Abstract

Photoacoustic imaging techniques have been extensively developed for biomedical applications, including functional and molecular imaging, due in part to their high optical contrast, high spatial resolution, and non-ionizing imaging properties. However, there are currently depth limitations in cellular-resolution, optically focused photoacoustic microscopy systems. In addition, most common photoacoustic systems need to be in contact with the sample through an ultrasound medium. In this work, by taking advantage of large photoacoustic initial pressures, all-optical non-contact optical resolution photoacoustic imaging is reported at depths beyond the optical transport mean-free path of the excitation wavelength. The proposed technique is called deep photoacoustic remote sensing (dPARS) microscopy. Visible pulsed excitation wavelengths are used to produce large initial-pressure-induced refractive index modulations in absorbing targets. These localized pressure rises create transient variations to the local scattering properties, which are detected as back-reflected intensity modulations from a deep-penetrating interrogation beam and do not require an interferometric detection pathway. Experiments demonstrate that dPARS is capable of providing optical resolution images to depths of 2.5 mm in tissue-mimicking scattering media. Signal-to-noise ratio 50dB is reported for in vivo imaging of microvascular networks. Also, imaging of single red blood cells, oxygen saturation mapping, and deep-vascular imaging applications are demonstrated. dPARS’s capabilities such as remote sensing, deep optical resolution imaging, and high signal-to-noise ratio, may yield new opportunities for several pre-clinical and clinical applications.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

1. INTRODUCTION

Photoacoustic (PA) imaging has demonstrated the capability to visualize absorbing structures in scattering media, to image microvasculature, estimate blood velocity and oxygen saturation, map neuro-function, visualize gene expression and contrast agent distributions, and monitor the efficacy of anti-angiogenic therapies [112]. While acoustic resolution PA imaging is capable of penetrating deep tissues, it cannot provide cellular resolution [13]. In order to achieve cellular resolution, optical-resolution PA microscopy (OR-PAM) has been developed by tightly focusing the excitation laser beam. However, this, in turn, restricts imaging depth to the transport mean-free path, typically <1mm in tissues [1317]. The transport mean-free path is the depth at which photon scattering directions become randomized and limits the penetration of ballistic optically focused microscopy systems. In addition, most PA technologies require acoustic coupling and contact with ultrasonic transducers. These limitations reduce the number of possible clinical and pre-clinical applications. Therefore, non-contact PA imaging is desirable [1826].

Our group recently found that PA initial pressures could be optically interrogated by measuring the intensity reflectivity modulations of a low-coherence probe beam [27]. These modulations were attributed to large changes in the reflection coefficient of an absorbing interface when PA initial pressures are generated. In this paper, we aim to utilize this new initial pressure detection mechanism to push the limits of sensitivity and break previous barriers of optical imaging depth. The key contributions include the following: (1) a non-contact cellular-resolution PA imaging system with high signal-to-noise ratio (SNR). This is accomplished in part, by using balanced photodetection. In vivo average SNR was measured to be 50dB. (2) Deep imaging is demonstrated. By taking advantage of a deep-penetrating short-wave infrared (SWIR) interrogation beam, optical resolution can be maintained beyond the transport mean-free path of the visible excitation beam. Phantom experiments demonstrate imaging to depths of 2.5 mm in tissue-mimicking media with 9-µm lateral resolution. It breaks previous barriers of imaging depth imposed by scattering by requiring only one-way focusing of deep-penetrating light while providing the optical contrast advantages of visible light. (3) Non-contact functional imaging of blood oxygenation is demonstrated.

The proposed non-interferometric approach is called deep PA remote sensing (dPARS) microscopy. dPARS, unlike optical coherence tomography (OCT), does not rely on detection of coherence-gated ballistic photons, but instead is tolerant of quasi-ballistic photons, permitting high signal-to-noise cellular-resolution imaging in deep multiply scattering media. PARS penetration depth may even exceed that of OCT, since PARS requires only one-way quasi-ballistic-focusing of photons, as opposed to the two-way ballistic focusing and coherence gating needed in OCT. Additionally, PARS provides absorption information not easily obtained in OCT, despite several notable developments using low-coherence visible light.

In vivo structural and functional imaging of microvascular networks, real-time imaging of single red blood cells (RBCs), oxygen saturation mapping, and deep-vascular imaging applications are demonstrated. The proposed dPARS approach could have major implications for a number of applications, including neuroscience, which is missing necessary toolsets for imaging single neurons in deep tissues below a millimeter depth. The proposed tool should open new opportunities for functional biology in model organisms as well as provide new opportunities for clinical translation.

2. MATERIALS AND METHODS

A model for pulsed excitation-induced modulation of the intensity reflection coefficient, RI of a planar interface was previously introduced by our group [27,28]. To a first-order approximation, the reflectivity modulation ΔRI was found to be proportional to the index step across the interface Δn, as well as the optical-absorption-induced initial pressure p0. These pressures can be very large due to stress confinement. An example calculation detailed in Section 1 of Supplement 1 predicts initial pressures of a RBC to be as large as 294 MPa. Considering a RBC-like–blood plasma planar interface leads to a relative change in reflected light of around ΔRIRI1.7 from the interface (Section 1 of Supplement 1).

The proposed approach transiently amplifies scattering from existing refractive index steps where absorption is present. While effective static signals from the probe beam occur due to inherent scattering and reflection, high-frequency modulations are present only when PA initial pressures are generated. By using a low-coherence probe beam and a non-interferometric detection system, we exclude phase sensitivity to propagating acoustic waves and are sensitive only to intensity reflectivity changes due to initial pressures [29,30].

Figure 1(a) shows the comparison of the PARS detection mechanism versus OR-PAM. PARS is sensitive to initial pressures, while OR-PAM is measuring the propagated ultrasound signals. Figure 1(b) shows two different modes of operation for PARS imaging: first, a high-resolution mode for visualizing superficial structures, and second, a deep-penetrating mode. The main difference between these two modes is the focused spot size of the excitation beam. For superficial structures, PARS excitation light is focused to a sub-micrometer spot size and dominates the lateral resolution. In the deep-imaging mode, the excitation beam is loosely focused and will be multiply scattered. Here the resolution is dominated by the deeply focused SWIR probe beam. The loose excitation focus ensures smaller divergence entering the sample and provides improved fluence at depths beyond the excitation transport mean-free path. For example, half angle divergence Θ, for a spot size of 3 µm is 0.11 mrad, while the Θ for a 200-µm spot size is 0.001mrad. This shows that deep-penetrating mode ensures delivery of more excitation fluence at depths beyond the transport mean-free path.

 figure: Fig. 1.

Fig. 1. dPARS mechanism. (a) PARS versus OR-PAM detection mechanism. PARS technology, unlike any other photoacoustic imaging systems, does not measure propagated ultrasound pressures but rather the initial pressure generated at the origin. (b) Comparison between two different PARS modes, a deep penetrating mode and a high-resolution mode. RBC: red blood cell. lt,Excitation= transport mean-free path of the excitation beam. lt,Probe= transport mean-free path of the probe beam.

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At superficial imaging depths, there is a three-way focusing effect provided by two-way detection focusing (transmit and receive), which is analogous to confocal microscopy, and an additional focus provided by the excitation. Beyond depths where the excitation focus can no longer be maintained, there will be a two-way focusing being provided by the interrogation beam, within the transport mean-free depth of the SWIR beam, even if the excitation beam is now broad. A simplified experimental setup is shown in Fig. 2(a). The fundamental 532-nm pulsed excitation beam is passed through a polarization-maintaining single-mode fiber to generate a stimulated Raman scattering (SRS) spectrum. The SRS spectrum can be modified by modulating the input power of the 532-nm laser light [31,32]. L1 and L2 are used to change the focused spot size of the excitation beam for two different modes proposed earlier. A 1310-nm continuous-wave (CW) low-coherence probe beam is used as the interrogation source. This beam is split such that a small component (<10%) is sent to one side of a balanced photodiode for the reference input, and the other 90% is passed towards the sample. Both beams are combined and co-aligned before passing through a 2D galvanometer scanning mirror system and being co-focused through an objective lens. The back-reflected component of the probe beam is returned through the system and directed to the remaining side of the balanced photodiode for balanced detection. Figure S1 in Supplement 1 shows a more detailed experimental setup.

 figure: Fig. 2.

Fig. 2. dPARS experimental setup and validation. (a) Simplified PARS apparatus. The fundamental 532-nm pulsed excitation beam is fed into a polarization-maintaining single-mode fiber (SMF), which can generate stimulated Raman scattering (SRS) broadening in the spectrum. The 1310-nm probe beam is split into the primary component made to be co-aligned with the excitation. The two beams are then co-scanned using a galvanometer mirror system or may be held stationary while scanning of the sample is performed with a motor stage (MS). The back-reflected probe beam is fed into one side of a balanced photodiode (BPD) and is compared with the smaller component of the original probe beam for balanced detection. Other system components: collimator (C), polarized beam splitter (PBS), beam splitter (BS), beam combiner (BC), attenuator (A), quarter wave plate (QWP), objective lens (OL), lens (L). (b) Image of carbon fiber networks using the deep penetrating imaging mode. (c) Image of carbon fiber networks using the high-resolution imaging mode, as well as an inset image of 100-nm gold nanoparticles. (d) Images of carbon fiber networks at various depths in tissue-mimicking solution.

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Figure 2(b) shows carbon fibers imaged with the deep-penetration mode. In this experiment, the excitation beam spot size was measured to be 200μm on the sample. However, optical resolution quality is maintained by focusing only the interrogation beam. The lateral resolution is measured to be 7μm as expected from the size of the detection beam. To demonstrate the high-resolution mode, carbon fiber networks and 100-nm gold nanoparticles (0.1mM PBS, 753688, Sigma-Aldrich) were imaged on a glass slide, as shown in Fig. 2(c). The resolution for the gold nanoparticles image is measured to be 670nm, close to the theoretical limit provided by the numerical aperture (NA)=0.4 objective lens for the excitation wavelength of 532 nm.

To investigate whether optical resolution can be maintained at significant depths beyond the transport mean-free path of the excitation beam, phantom imaging experiments were performed by imaging carbon fiber networks in an intralipid scattering solution. In Fig. 2(d), carbon fiber networks were immobilized between two 100-µm glass coverslips. 1% intralipid solution was used above the sample as a tissue-mimicking medium. The carbon fiber networks could be imaged with an optical resolution down to 2.5 mm, which is close to the transport mean-free path of the detection beam (see Supplement 1, Section 3). The results shown in Fig. 2(d) prove that optically focused PARS penetration depth can be extended by taking advantage of the deep-reaching SWIR beam. For example, in soft tissue, the transport mean-free paths are calculated as: lt(λex=532nm)=0.57mm and lt(λint=1310nm)=1.43mm. This means dPARS can extend the optically focused penetration depth >2.5 times over OR-PAM modalities using visible excitation. OR-PAM has also used near-IR (NIR) excitation light to achieve penetration deeper than is possible with visible light at the cost of significantly less absorption contrast. The dPARS approach offers the penetration of SWIR light with the imaging contrast advantages of visible light excitation.

While OR-PAM can also employ an NIR source for excitation to improve penetration depth, this comes at the cost of significantly lower molar extinction from hemoglobin and impacts sensitivity. Nevertheless, Hai et al. [33] demonstrated deep OR-PAM structural imaging of deep (up to 750 µm) vasculature with 1046-nm excitation and imaging of a black human hair to depths of 3.2 mm in chicken tissue with 48-µm lateral resolution and 6-dB SNR. Imaging at greater depths has been demonstrated only with acoustic rather than optical resolution. Deep functional oxygen saturation imaging with NIR OR-PAM has yet to be demonstrated, but others [34] used visible wavelengths at depths sufficient for transcranial functional imaging in mice, an accomplishment not yet achieved with other purely optical approaches, such as two-photon microscopy. Hu et al. [16] demonstrated imaging of a black needle to depths of 1.2 mm in tissue using a second-generation OR-PAM system with 570-nm excitation. The proposed approach offers the advantages of strong optical absorption due to visible excitation along with the deep readout advantages of 1310-nm light. We demonstrate in vivo imaging of vasculature to depths of 1.2 mm in vivo with intralipid phantom imaging demonstrated to depths of 2.5 mm. The deep penetration of dPARS may be comparable to NIR OR-PAM but additionally comes with advantages of being non-contact.

A. Image Formation

The beams can be scanned using 2D galvanometer mirrors to provide real-time imaging, or they can be held stationary while the sample is scanned using a two-axis mechanical motor stage system for larger scan areas. The galvanometer scanning mirror system used fixed fast and slow scanning rates of 65 Hz and 0.25 Hz. Large field-of-view images were formed by using two-axis mechanical scanning and were performed with a 2.5-µm step size at a 2.5-kHz acquisition rate. For example, to produce a 4mm×4mm scan, it takes roughly 17 min. The pulse repetition rate of the excitation laser was fixed at 40 KHz for all the images shown in the paper.

3. RESULTS AND DISCUSSION

Figures 3(a) and 3(b) are formed by using the high-resolution PARS imaging mode. Figure 3(a) shows in vivo PARS images of en face microvasculature in the ear of an 8-week-old athymic nude mouse (NU/NU, Charles River, MA, USA). Figure 3(b) shows RBCs imaged in the mouse ear using fast galvanometer scanning. Figure 3(c) shows in vivo PARS images of en face microvasculature in the ear of an 8-week-old nude mouse using the deep-penetrating mode, since the mouse ear thickness is usually about a few hundred micrometers. Figure 3(d) shows in vivo PARS images of en face microvasculature in the tip of the mouse ear using high-resolution mode. Deeper vasculature in the back flank of a mouse is imaged as shown in Fig. 3(e).

 figure: Fig. 3.

Fig. 3. In vivo PARS microscopy structural images. (a) Image of en face microvasculature in the ear of an 8-week-old nude mouse (NU/NU, Charles River, MA, USA) using the high-resolution mode (scale bar: 500 µm) (b) In vivo image of red blood cells in the mouse ear using the high-resolution mode (scale bar: 5 µm) (c) Image of mouse ear vasculature using the deep-penetrating mode (scale bar: 500 µm) (d) Image of en face microvasculature in the tip of a mouse ear (NU/NU, Charles River, MA, USA) using the high-resolution mode (scale bar: 500 µm) (e) Images of back flank of mouse at various depths using the deep-penetrating mode (scale bar: 100 µm).

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In these images, the imaging spot size first was fixed at the skin surface of the animal, then by using a precise Z-stage, separate images were recorded at each depth. PARS microscopy may provide significant depth advantages over other forms of visible-light microscopy, including visible-wavelength OCT [35]. All the experimental procedures were carried out in conformity with the laboratory animal protocol approved by the University of Alberta Animal Use and Care Committee. Authors are also trained and certified in order to use mice and rats in the research work. During the imaging sessions, animals were anaesthetized with isoflurane using a breathing anesthesia system (E-Z Anesthesia, Euthanex Corp.).

For images at depths shallower than 1 mm, a pulse energy of 50nJ was used with interrogation power fixed at 5 mW. For images at longer depths, a pulse energy of 60nJ was used with interrogation power fixed at 6 mW. In the deep-penetrating mode, higher pulse energy and interrogation power were used to compensate for the sensitivity drop due to lower focal fluence. For depths below the transport mean-free pathlength of the excitation light, fluence cannot be optically focused. If we assume that 50% of American National Standards Institute (ANSI)-level light reaches the target (10mJ/cm2), the initial pressure rise will be <6MPa in blood cells, leading to an estimated 3% change in intensity reflection coefficient. The SNR of the large vessels (average of maximum-amplitude-projection pixels in a region of interest over the standard deviation of the noise, measured in a separate region with no vessels) is measured as 50dB.

Figure 4 shows SO2 measurement of a mouse ear using spectra generated using SRS in a single-mode fiber, similar to previous contact-based OR-PAM work [31,32]. 545-nm and 580-nm wavelengths are filtered and used for SO2 measurement, as shown in Fig. 4. Arteriole SO2 is consistent with pulse oximetry measurements monitored simultaneously during the imaging session.

 figure: Fig. 4.

Fig. 4. Functional images SO2 measurement of en face microvasculature in the ear of an 8-week-old nude mouse (NU/NU, Charles River, MA, USA).

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PARS microscopy is a fundamentally new paradigm for optical imaging with combined absorption and scattering contrast and offers potential advantages over other modalities. Traditional spectroscopic unmixing methods with positivity constraints has been applied, similar to [8]. The current methods for spectroscopic unmixing and SO2 estimation are similar to previous work using OR-PAM. However, these methods may suffer from limitations of wavelength-dependent fluence and other considerations. Sources of error in SO2 estimates using PARS should be investigated in future work. By virtue of the low-coherence interrogation beam and time gating, all effective sources of non-local signal are rejected and only intensity modulations due to initial pressures are detected. PARS offers capabilities similar to OR-PAM but with the potential for greater imaging depth for visible excitations while using a non-contact implementation. Additionally, imaging speed can potentially be much faster than other PA modalities, as the PARS approach is not time limited by acoustic propagation.

Future work will push limits of imaging speed, which could lead to A-line imaging rates of tens to hundreds of MHz. Additional work should also involve extending depths using even further-penetrating wavelengths, such as 1700 nm. Further development should also demonstrate molecular contrast using fluorescent proteins and chromoproteins. Applications may include deep brain imaging, dermatological and gastroenterological applications, surgical navigation imaging for vascular patency evaluation, non-contact blood oxygen monitoring, and many other clinical and pre-clinical applications.

Unlike conventional PA techniques, the proposed approach is unable to provide time-resolved signals with depth discrimination. Therefore, the axial resolution is determined by optical sectioning. This is in turn dependent on the depth of focus (DOF) of the beams. The theoretical Gaussian-beam depth of focus in free space is calculated as DOF=2λ0πNA2. Thus, at superficial depths where the 532-nm excitation beam will dominate the resolution, the theoretical DOF is 2.2 µm, and at deeper penetration depths where 1310 nm dominates (and the 532-nm light is multiply scattered) DOF is 5.2 µm, calculated for NA=0.4 used in experiments. These are best-case theoretical values. In practice, if the excitation and interrogation beams focus at different depths (e.g., due to chromatic aberration or misalignment) the effective DOF can be much longer. In addition, the objective lens is illuminated with a beam that does not fully occupy the pupil to accommodate optical scanning, so the effective NA is reduced. Additionally, in scattering media at depths beyond a mean-free path, the focal fluence is expected to be additionally blurred due to multiple scattering. The DOF is experimentally measured as 30±5μm from scans of carbon fibers at a depth of 480 µm in gelatin. In deep scattering media, this may be substantially longer owing to multiple scattering. The measured 30±5μm DOF may still be applicable at shallow depths in scattering media where light transport is primarily ballistic.

Depth-resolved volume scanning presently must be done by scanning layer by layer. In the future, depth information may be recoverable without such time-consuming depth scanning through the addition of coherence gating [36]. In the present work, a maximum-amplitude projection (MAP) C-scan is presented from PARS scans using a single focal depth. Such MAP C-scans are widely used, even for depth-resolved modalities. When only MAP C-scans are desired, the poor depth discrimination of PARS may be of little consequence. For a fixed laser repetition rate, PARS MAP C-scan acquisition rates are comparable with fast OR-PAM scanning rates [3739]. With higher repetition rates, PARS could even exceed OR-PAM imaging speeds, given that PARS is not frame-rate limited by acoustic time of flight to an external transducer [40].

Present functional imaging capabilities are limited to superficial vasculature. As is the case for deep OR-PAM, PARS functional imaging at non-superficial depths may prove challenging and will require further investigation. Future challenges to be addressed for deep functional imaging include unknown wavelength-dependent fluence and weak SNRs, which likewise are challenging for other PA methods. Future improvements in SNR and fluence compensation will be needed for deep functional imaging capabilities.

A. Image Processing

All the 2D images shown in this paper were formed using a MAP from the Hilbert transform of each A-scan as a pixel in a C-scan en face image. All images shown in this paper were produced either by direct plotting of raw data (mechanical scanning of the sample) or from interpolated raw data (mirror scanning of interrogation spot) followed by 3×3 median filtering and Frangi vesselness filtering [41]. SNR measurements were performed on raw data prior to image processing. In the case of galvanometer scanning, a Delaunay triangulation interpolation algorithm was used to render the data acquired on a sinusoidal trajectory onto a Cartesian grid. All image and signal processing steps were performed in the MATLAB environment.

B. Laser Safety

1. Excitation Beam Laser Safety

The pulse energy of the excitation beam for in vivo PARS imaging has been set as 50 nJ, with calculated surface laser fluence 0.6mJ/cm2, which is below the single pulse limit of 20mJ/cm2 set by the ANSI [42]. Considering maximum permissible exposure (MPE) for a pulse train, our surface fluence is about 10 times lower than the ANSI limit. The spatial peak optical fluence at the focus is 710mJ/cm2, which is still less than the damage threshold observed in small animals and comparable to other OR-PAM systems. In our work, light delivery is confined to a localized area, and no tissue damage is visible after imaging [27].

2. Interrogation Beam Laser Safety Considerations

Optical scanning on a 1mm×1mm or smaller area with a laser power of 5 mW was performed. The average surface power of 0.5W/cm2 is about six times lower than the average power ANSI limit of 3W/cm2, when considering a fast-axis galvanometer scanning rate of 60 Hz and a slow-axis scanning rate of 0.25 Hz (half C-scan frames per second) over 1 mm field of view (FOV). Considering laser beam overlapping at the skin surface when the interrogation beam is focused at 150μm and 1mm underneath the skin, the fluence on the skin surface in our experiments can be calculated as 64W/cm2 and 1W/cm2, which are 2 times and 5 times lower than the ANSI limits of 103W/cm2 and 5W/cm2, respectively.

4. CONCLUSION

A novel non-contact reflection mode optical resolution imaging system has been demonstrated with sensitivity to optical absorption and unprecedented optically focused imaging depth capabilities. The system capitalizes on detection of transiently amplified scattering from existing refractive index steps where absorption is present. By using SWIR interrogation beams, deep penetration is achieved while maintaining optical resolution and visible-wavelength absorption contrast. This enables about 2.5 times deeper imaging capabilities compared to other optical-resolution visible-wavelength excitation modalities. Non-contact functional oxygen-saturation estimation was demonstrated in living subjects. The proposed system’s novel depth capabilities, high SNR, and non-contact methodology may lead to numerous practical applications in a wide range of pre-clinical and clinical settings.

Funding

Natural Sciences and Engineering Research Council of Canada (NSERC) (355544-2008, 375340-2009, STPGP 396444); Alberta Innovates Health Solutions AIHS CRIO Team (201201154); Alberta Cancer Research Institute (ACB 23728); Canada Foundation for Innovation (CFI), Leaders Opportunity Fund (18472); Small Equipment Grants Program, Alberta Advanced Education & Technology (URSI09007SEG).

Acknowledgment

We gratefully acknowledge Alberta Ingenuity/Alberta Innovates scholarships for graduate and undergraduate students and an Alberta Innovates Technology Futures Postdoctoral Fellowship. We also thank Min Choi for helping with oxygen measurements. We also acknowledge fruitful discussions with Prof. Robert Fedosejevs.

 

See Supplement 1 for supporting content.

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36. K. L. Bell, P. Hajireza, and R. Zemp, “Coherence-gated photoacoustic remote sensing microscopy (Conference Presentation),” Proc. SPIE 10494, 1049422 (2018). [CrossRef]  

37. L. Li, C. Yeh, S. Hu, L. Wang, B. T. Soetikno, R. Chen, Q. Zhou, K. K. Shung, K. I. Maslov, and L. V. Wang, “Fully motorized optical-resolution photoacoustic microscopy,” Opt. Lett. 39, 2117–2120 (2014). [CrossRef]  

38. B. Ning, M. J. Kennedy, A. J. Dixon, N. Sun, R. Cao, B. T. Soetikno, R. Chen, Q. Zhou, K. K. Shung, J. A. Hossack, and S. Hu, “Simultaneous photoacoustic microscopy of microvascular anatomy, oxygen saturation, and blood flow,” Opt. Lett. 40, 910–913 (2015). [CrossRef]  

39. Y. He, L. Wang, J. Shi, J. Yao, L. Li, R. Zhang, C.-H. Huang, J. Zou, and L. V. Wang, “In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells,” Sci. Rep. 6, 39616 (2016). [CrossRef]  

40. L. Snider, K. Bell, P. Reza, and R. J. Zemp, “Toward wide-field high-speed photoacoustic remote sensing microscopy,” Proc. SPIE 10494, 1049423 (2018). [CrossRef]  

41. A. F. Frangi, W. J. Niessen, K. L. Vincken, and M. A. Viergever, Medical Image Computing and Computer-Assisted Intervention — MICCAI’98: First International Conference Cambridge, MA, USA, October 11–13, 1998 Proceedings, W. M. Wells, A. Colchester, and S. Delp, eds. (Springer, 1998), pp. 130–137.

42. Laser Institute of America, “American National Standard for Safe Use of Lasers,” ANSI Z136.1 (2007).

References

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  4. J. Yang, C. Favazza, R. Chen, J. Yao, S. Cai, K. Maslov, Q. Zhou, K. Shung, and L. Wang, “Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo,” Nat. Med. 18, 1297–1302 (2012).
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  5. L. V. Wang, “Multiscale photoacoustic microscopy and computed tomography,” Nat. Photonics 3, 503–509 (2009).
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  6. J. Yao, L. Wang, J. M. K. Yang, K. I. Maslov, T. T. Wong, L. Li, C.-H. Huang, J. Zuo, and L. V. Wang, “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods 12, 407–410 (2015).
    [Crossref]
  7. H. F. Zhang, K. Maslov, G. Stoica, and L. V. Wang, “Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging,” Nat. Biotechnol. 24, 848–851 (2006).
    [Crossref]
  8. R. J. Paproski, A. Heinmiller, K. Wachowicz, and R. J. Zemp, “Multi-wavelength photoacoustic imaging of inducible tyrosinase reporter gene expression in xenograft tumors,” Sci. Rep. 4, 5329 (2014).
    [Crossref]
  9. D. Wu, L. Huang, M. S. Jiang, and H. Jiang, “Contrast agents for photoacoustic and thermoacoustic imaging: a review,” Int. J. Mol. Sci. 15, 23616–23639 (2014).
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  10. E. M. Strohm, M. J. Moore, and M. C. Kolios, “Single cell photoacoustic microscopy: a review,” IEEE J. Sel. Top. Quantum Electron. 22, 137–151 (2016).
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  15. P. Hajireza, W. Shi, and R. Zemp, “Label-free in vivo GRIN-lens optical resolution photoacoustic micro-endoscopy,” Laser Phys. Lett. 10, 055603 (2013).
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  18. Y. Wang, C. Li, and R. K. Wang, “Noncontact photoacoustic imaging achieved by using a low-coherence interferometer as the acoustic detector,” Opt. Lett. 36, 3975–3977 (2011).
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  19. A. Hochreiner, J. Bauer-Marschallinger, P. Burgholzer, B. Jakoby, and T. Berer, “Non-contact photoacoustic imaging using a fiber based interferometer with optical amplification,” Biomed. Opt. Express 4, 2322–2331 (2013).
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  20. G. Rousseau, A. Blouin, and J.-P. Monchalin, “Non-contact photoacoustic tomography and ultrasonography for tissue imaging,” Biomed. Opt. Express 3, 16–25 (2012).
    [Crossref]
  21. G. Rousseau, B. Gauthier, A. Blouin, and J.-P. Monchalin, “Non-contact biomedical photoacoustic and ultrasound imaging,” J. Biomed. Opt. 17, 061217 (2012).
    [Crossref]
  22. Z. Chen, S. Yang, Y. Wang, and D. Xing, “Noncontact broadband all-optical photoacoustic microscopy based on a low-coherence interferometer,” Appl. Phys. Lett. 106, 043701 (2015).
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  23. R. Nuster, P. Slezak, and G. Paltauf, “High resolution three-dimensional photoacoustic tomography with CCD-camera based ultrasound detection,” Biomed. Opt. Express 5, 2635–2647 (2014).
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  25. T. Berer, A. Hochreiner, S. Zamiri, and P. Burgholzer, “Remote photoacoustic imaging on solid material using a two-wave mixing interferometer,” Opt. Lett. 35, 4151–4153 (2010).
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  26. S. A. Carp and V. Venugopalan, “Optoacoustic imaging based on the interferometric measurement of surface displacement,” J. Biomed. Opt. 12, 064001 (2007).
    [Crossref]
  27. P. Hajireza, W. Shi, K. Bell, R. Paproski, and R. Zemp, “Non-interferometric photoacoustic remote sensing microscopy,” Light Sci. Appl. 6, e16278 (2017).
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  28. K. Bell, P. Hajireza, P. Shi, and R. Zemp, “Temporal evolution of low-coherence reflectrometry signals in photoacoustic remote sensing microscopy,” Appl. Opt. 56, 5172–5181 (2017).
    [Crossref]
  29. K. Bell, P. Hajireza, and R. Zemp, “Scattering cross-sectional modulation in photoacoustic remote sensing microscopy,” Opt. Lett. 43, 146–149 (2018).
    [Crossref]
  30. J. Yao, “When pressure meets light: detecting the photoacoustic effect at the origin,” Light Sci. Appl. 6, e17062 (2017).
    [Crossref]
  31. P. Hajireza, A. Forbrich, and R. J. Zemp, “Multifocus optical-resolution photoacoustic microscopy using stimulated Raman scattering and chromatic aberration,” Opt. Lett. 38, 2711–2713 (2013).
    [Crossref]
  32. P. Hajireza, A. Forbrich, and R. Zemp, “In-vivo functional optical-resolution photoacoustic microscopy with stimulated Raman scattering fiber-laser source,” Biomed. Opt. Express 5, 539–546 (2014).
    [Crossref]
  33. P. Hai, J. Yao, K. I. Maslov, Y. Zhou, and L. V. Wang, “Near-infrared optical-resolution photoacoustic microscopy,” Opt. Lett. 39, 5192–5195 (2014).
    [Crossref]
  34. S. Hu, K. I. Maslov, V. Tsytsarev, and L. V. Wang, “Functional transcranial brain imaging by optical-resolution photoacoustic microscopy,” J. Biomed. Opt. 14, 040503 (2009).
    [Crossref]
  35. J. Yi, W. Liu, S. Chen, V. Backman, N. Sheibani, C. M. Sorenson, A. A. Fawzi, R. A. Linsenmeier, and H. F. Zhang, “Visible light optical coherence tomography measures retinal oxygen metabolic response to systemic oxygenation,” Light Sci. Appl. 4, e334 (2015).
    [Crossref]
  36. K. L. Bell, P. Hajireza, and R. Zemp, “Coherence-gated photoacoustic remote sensing microscopy (Conference Presentation),” Proc. SPIE 10494, 1049422 (2018).
    [Crossref]
  37. L. Li, C. Yeh, S. Hu, L. Wang, B. T. Soetikno, R. Chen, Q. Zhou, K. K. Shung, K. I. Maslov, and L. V. Wang, “Fully motorized optical-resolution photoacoustic microscopy,” Opt. Lett. 39, 2117–2120 (2014).
    [Crossref]
  38. B. Ning, M. J. Kennedy, A. J. Dixon, N. Sun, R. Cao, B. T. Soetikno, R. Chen, Q. Zhou, K. K. Shung, J. A. Hossack, and S. Hu, “Simultaneous photoacoustic microscopy of microvascular anatomy, oxygen saturation, and blood flow,” Opt. Lett. 40, 910–913 (2015).
    [Crossref]
  39. Y. He, L. Wang, J. Shi, J. Yao, L. Li, R. Zhang, C.-H. Huang, J. Zou, and L. V. Wang, “In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells,” Sci. Rep. 6, 39616 (2016).
    [Crossref]
  40. L. Snider, K. Bell, P. Reza, and R. J. Zemp, “Toward wide-field high-speed photoacoustic remote sensing microscopy,” Proc. SPIE 10494, 1049423 (2018).
    [Crossref]
  41. A. F. Frangi, W. J. Niessen, K. L. Vincken, and M. A. Viergever, Medical Image Computing and Computer-Assisted Intervention — MICCAI’98: First International Conference Cambridge, MA, USA, October 11–13, 1998 Proceedings, W. M. Wells, A. Colchester, and S. Delp, eds. (Springer, 1998), pp. 130–137.
  42. Laser Institute of America, “American National Standard for Safe Use of Lasers,” (2007).

2018 (3)

K. Bell, P. Hajireza, and R. Zemp, “Scattering cross-sectional modulation in photoacoustic remote sensing microscopy,” Opt. Lett. 43, 146–149 (2018).
[Crossref]

K. L. Bell, P. Hajireza, and R. Zemp, “Coherence-gated photoacoustic remote sensing microscopy (Conference Presentation),” Proc. SPIE 10494, 1049422 (2018).
[Crossref]

L. Snider, K. Bell, P. Reza, and R. J. Zemp, “Toward wide-field high-speed photoacoustic remote sensing microscopy,” Proc. SPIE 10494, 1049423 (2018).
[Crossref]

2017 (3)

J. Yao, “When pressure meets light: detecting the photoacoustic effect at the origin,” Light Sci. Appl. 6, e17062 (2017).
[Crossref]

P. Hajireza, W. Shi, K. Bell, R. Paproski, and R. Zemp, “Non-interferometric photoacoustic remote sensing microscopy,” Light Sci. Appl. 6, e16278 (2017).
[Crossref]

K. Bell, P. Hajireza, P. Shi, and R. Zemp, “Temporal evolution of low-coherence reflectrometry signals in photoacoustic remote sensing microscopy,” Appl. Opt. 56, 5172–5181 (2017).
[Crossref]

2016 (3)

E. M. Strohm, M. J. Moore, and M. C. Kolios, “Single cell photoacoustic microscopy: a review,” IEEE J. Sel. Top. Quantum Electron. 22, 137–151 (2016).
[Crossref]

J. Yao, A. A. Kaberniuk, L. Li, D. M. Shcherbakova, R. Zhang, L. Wang, G. Li, V. V. Verkhusha, and L. V. Wang, “Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe,” Nat. Methods 13, 67–73 (2016).
[Crossref]

Y. He, L. Wang, J. Shi, J. Yao, L. Li, R. Zhang, C.-H. Huang, J. Zou, and L. V. Wang, “In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells,” Sci. Rep. 6, 39616 (2016).
[Crossref]

2015 (5)

B. Ning, M. J. Kennedy, A. J. Dixon, N. Sun, R. Cao, B. T. Soetikno, R. Chen, Q. Zhou, K. K. Shung, J. A. Hossack, and S. Hu, “Simultaneous photoacoustic microscopy of microvascular anatomy, oxygen saturation, and blood flow,” Opt. Lett. 40, 910–913 (2015).
[Crossref]

P. Hajireza, J. Sorge, M. Brett, and R. Zemp, “In vivo optical resolution photoacoustic microscopy using glancing angle-deposited nanostructured Fabry-Perot etalons,” Opt. Lett. 40, 1350–1353 (2015).
[Crossref]

J. Yao, L. Wang, J. M. K. Yang, K. I. Maslov, T. T. Wong, L. Li, C.-H. Huang, J. Zuo, and L. V. Wang, “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods 12, 407–410 (2015).
[Crossref]

Z. Chen, S. Yang, Y. Wang, and D. Xing, “Noncontact broadband all-optical photoacoustic microscopy based on a low-coherence interferometer,” Appl. Phys. Lett. 106, 043701 (2015).
[Crossref]

J. Yi, W. Liu, S. Chen, V. Backman, N. Sheibani, C. M. Sorenson, A. A. Fawzi, R. A. Linsenmeier, and H. F. Zhang, “Visible light optical coherence tomography measures retinal oxygen metabolic response to systemic oxygenation,” Light Sci. Appl. 4, e334 (2015).
[Crossref]

2014 (7)

2013 (4)

L. Wang, K. Maslov, and L. V. Wang, “Single-cell label-free photoacoustic flowoxigraphy in vivo,” Proc. Natl. Acad. Sci. USA 110, 5759–5764 (2013).
[Crossref]

P. Hajireza, W. Shi, and R. Zemp, “Label-free in vivo GRIN-lens optical resolution photoacoustic micro-endoscopy,” Laser Phys. Lett. 10, 055603 (2013).
[Crossref]

A. Hochreiner, J. Bauer-Marschallinger, P. Burgholzer, B. Jakoby, and T. Berer, “Non-contact photoacoustic imaging using a fiber based interferometer with optical amplification,” Biomed. Opt. Express 4, 2322–2331 (2013).
[Crossref]

P. Hajireza, A. Forbrich, and R. J. Zemp, “Multifocus optical-resolution photoacoustic microscopy using stimulated Raman scattering and chromatic aberration,” Opt. Lett. 38, 2711–2713 (2013).
[Crossref]

2012 (3)

G. Rousseau, A. Blouin, and J.-P. Monchalin, “Non-contact photoacoustic tomography and ultrasonography for tissue imaging,” Biomed. Opt. Express 3, 16–25 (2012).
[Crossref]

G. Rousseau, B. Gauthier, A. Blouin, and J.-P. Monchalin, “Non-contact biomedical photoacoustic and ultrasound imaging,” J. Biomed. Opt. 17, 061217 (2012).
[Crossref]

J. Yang, C. Favazza, R. Chen, J. Yao, S. Cai, K. Maslov, Q. Zhou, K. Shung, and L. Wang, “Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo,” Nat. Med. 18, 1297–1302 (2012).
[Crossref]

2011 (5)

2010 (1)

2009 (2)

S. Hu, K. I. Maslov, V. Tsytsarev, and L. V. Wang, “Functional transcranial brain imaging by optical-resolution photoacoustic microscopy,” J. Biomed. Opt. 14, 040503 (2009).
[Crossref]

L. V. Wang, “Multiscale photoacoustic microscopy and computed tomography,” Nat. Photonics 3, 503–509 (2009).
[Crossref]

2008 (1)

2007 (2)

S. A. Carp and V. Venugopalan, “Optoacoustic imaging based on the interferometric measurement of surface displacement,” J. Biomed. Opt. 12, 064001 (2007).
[Crossref]

G. Paltauf, R. Nuster, M. Haltmeier, and P. Burgholzer, “Photoacoustic tomography using a Mach-Zehnder interferometer as an acoustic line detector,” Appl. Opt. 46, 3352–3358 (2007).
[Crossref]

2006 (1)

H. F. Zhang, K. Maslov, G. Stoica, and L. V. Wang, “Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging,” Nat. Biotechnol. 24, 848–851 (2006).
[Crossref]

Backman, V.

J. Yi, W. Liu, S. Chen, V. Backman, N. Sheibani, C. M. Sorenson, A. A. Fawzi, R. A. Linsenmeier, and H. F. Zhang, “Visible light optical coherence tomography measures retinal oxygen metabolic response to systemic oxygenation,” Light Sci. Appl. 4, e334 (2015).
[Crossref]

Bauer-Marschallinger, J.

Beard, P.

P. Beard, “Biomedical photoacoustic imaging,” Interface Focus 1, 602–631 (2011).
[Crossref]

Bell, K.

K. Bell, P. Hajireza, and R. Zemp, “Scattering cross-sectional modulation in photoacoustic remote sensing microscopy,” Opt. Lett. 43, 146–149 (2018).
[Crossref]

L. Snider, K. Bell, P. Reza, and R. J. Zemp, “Toward wide-field high-speed photoacoustic remote sensing microscopy,” Proc. SPIE 10494, 1049423 (2018).
[Crossref]

P. Hajireza, W. Shi, K. Bell, R. Paproski, and R. Zemp, “Non-interferometric photoacoustic remote sensing microscopy,” Light Sci. Appl. 6, e16278 (2017).
[Crossref]

K. Bell, P. Hajireza, P. Shi, and R. Zemp, “Temporal evolution of low-coherence reflectrometry signals in photoacoustic remote sensing microscopy,” Appl. Opt. 56, 5172–5181 (2017).
[Crossref]

Bell, K. L.

K. L. Bell, P. Hajireza, and R. Zemp, “Coherence-gated photoacoustic remote sensing microscopy (Conference Presentation),” Proc. SPIE 10494, 1049422 (2018).
[Crossref]

Berer, T.

Blouin, A.

G. Rousseau, A. Blouin, and J.-P. Monchalin, “Non-contact photoacoustic tomography and ultrasonography for tissue imaging,” Biomed. Opt. Express 3, 16–25 (2012).
[Crossref]

G. Rousseau, B. Gauthier, A. Blouin, and J.-P. Monchalin, “Non-contact biomedical photoacoustic and ultrasound imaging,” J. Biomed. Opt. 17, 061217 (2012).
[Crossref]

Brett, M.

Burgholzer, P.

Cai, S.

J. Yang, C. Favazza, R. Chen, J. Yao, S. Cai, K. Maslov, Q. Zhou, K. Shung, and L. Wang, “Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo,” Nat. Med. 18, 1297–1302 (2012).
[Crossref]

Cao, R.

Carp, S. A.

S. A. Carp and V. Venugopalan, “Optoacoustic imaging based on the interferometric measurement of surface displacement,” J. Biomed. Opt. 12, 064001 (2007).
[Crossref]

Chen, R.

Chen, S.

J. Yi, W. Liu, S. Chen, V. Backman, N. Sheibani, C. M. Sorenson, A. A. Fawzi, R. A. Linsenmeier, and H. F. Zhang, “Visible light optical coherence tomography measures retinal oxygen metabolic response to systemic oxygenation,” Light Sci. Appl. 4, e334 (2015).
[Crossref]

Chen, Z.

Z. Chen, S. Yang, Y. Wang, and D. Xing, “Noncontact broadband all-optical photoacoustic microscopy based on a low-coherence interferometer,” Appl. Phys. Lett. 106, 043701 (2015).
[Crossref]

Dixon, A. J.

Favazza, C.

J. Yang, C. Favazza, R. Chen, J. Yao, S. Cai, K. Maslov, Q. Zhou, K. Shung, and L. Wang, “Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo,” Nat. Med. 18, 1297–1302 (2012).
[Crossref]

Fawzi, A. A.

J. Yi, W. Liu, S. Chen, V. Backman, N. Sheibani, C. M. Sorenson, A. A. Fawzi, R. A. Linsenmeier, and H. F. Zhang, “Visible light optical coherence tomography measures retinal oxygen metabolic response to systemic oxygenation,” Light Sci. Appl. 4, e334 (2015).
[Crossref]

Forbrich, A.

Frangi, A. F.

A. F. Frangi, W. J. Niessen, K. L. Vincken, and M. A. Viergever, Medical Image Computing and Computer-Assisted Intervention — MICCAI’98: First International Conference Cambridge, MA, USA, October 11–13, 1998 Proceedings, W. M. Wells, A. Colchester, and S. Delp, eds. (Springer, 1998), pp. 130–137.

Gao, L.

L. V. Wang and L. Gao, “Photoacoustic microscopy and computed tomography: from bench to bedside,” Annu. Rev. Biomed. Eng. 16, 155–185 (2014).
[Crossref]

Gauthier, B.

G. Rousseau, B. Gauthier, A. Blouin, and J.-P. Monchalin, “Non-contact biomedical photoacoustic and ultrasound imaging,” J. Biomed. Opt. 17, 061217 (2012).
[Crossref]

Hai, P.

Hajireza, P.

K. Bell, P. Hajireza, and R. Zemp, “Scattering cross-sectional modulation in photoacoustic remote sensing microscopy,” Opt. Lett. 43, 146–149 (2018).
[Crossref]

K. L. Bell, P. Hajireza, and R. Zemp, “Coherence-gated photoacoustic remote sensing microscopy (Conference Presentation),” Proc. SPIE 10494, 1049422 (2018).
[Crossref]

K. Bell, P. Hajireza, P. Shi, and R. Zemp, “Temporal evolution of low-coherence reflectrometry signals in photoacoustic remote sensing microscopy,” Appl. Opt. 56, 5172–5181 (2017).
[Crossref]

P. Hajireza, W. Shi, K. Bell, R. Paproski, and R. Zemp, “Non-interferometric photoacoustic remote sensing microscopy,” Light Sci. Appl. 6, e16278 (2017).
[Crossref]

P. Hajireza, J. Sorge, M. Brett, and R. Zemp, “In vivo optical resolution photoacoustic microscopy using glancing angle-deposited nanostructured Fabry-Perot etalons,” Opt. Lett. 40, 1350–1353 (2015).
[Crossref]

P. Hajireza, A. Forbrich, and R. Zemp, “In-vivo functional optical-resolution photoacoustic microscopy with stimulated Raman scattering fiber-laser source,” Biomed. Opt. Express 5, 539–546 (2014).
[Crossref]

P. Hajireza, A. Forbrich, and R. J. Zemp, “Multifocus optical-resolution photoacoustic microscopy using stimulated Raman scattering and chromatic aberration,” Opt. Lett. 38, 2711–2713 (2013).
[Crossref]

P. Hajireza, W. Shi, and R. Zemp, “Label-free in vivo GRIN-lens optical resolution photoacoustic micro-endoscopy,” Laser Phys. Lett. 10, 055603 (2013).
[Crossref]

P. Hajireza, W. Shi, and R. J. Zemp, “Label-free in vivo fiber-based optical-resolution photoacoustic microscopy,” Opt. Lett. 36, 4107–4109 (2011).
[Crossref]

P. Hajireza, W. Shi, and R. J. Zemp, “Real-time handheld optical-resolution photoacoustic microscopy,” Opt. Express 19, 20097–20102 (2011).
[Crossref]

Haltmeier, M.

He, Y.

Y. He, L. Wang, J. Shi, J. Yao, L. Li, R. Zhang, C.-H. Huang, J. Zou, and L. V. Wang, “In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells,” Sci. Rep. 6, 39616 (2016).
[Crossref]

Heinmiller, A.

R. J. Paproski, A. Heinmiller, K. Wachowicz, and R. J. Zemp, “Multi-wavelength photoacoustic imaging of inducible tyrosinase reporter gene expression in xenograft tumors,” Sci. Rep. 4, 5329 (2014).
[Crossref]

Hochreiner, A.

Hossack, J. A.

Hu, S.

Huang, C.-H.

Y. He, L. Wang, J. Shi, J. Yao, L. Li, R. Zhang, C.-H. Huang, J. Zou, and L. V. Wang, “In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells,” Sci. Rep. 6, 39616 (2016).
[Crossref]

J. Yao, L. Wang, J. M. K. Yang, K. I. Maslov, T. T. Wong, L. Li, C.-H. Huang, J. Zuo, and L. V. Wang, “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods 12, 407–410 (2015).
[Crossref]

Huang, L.

D. Wu, L. Huang, M. S. Jiang, and H. Jiang, “Contrast agents for photoacoustic and thermoacoustic imaging: a review,” Int. J. Mol. Sci. 15, 23616–23639 (2014).
[Crossref]

Jakoby, B.

Jiang, H.

D. Wu, L. Huang, M. S. Jiang, and H. Jiang, “Contrast agents for photoacoustic and thermoacoustic imaging: a review,” Int. J. Mol. Sci. 15, 23616–23639 (2014).
[Crossref]

Jiang, M. S.

D. Wu, L. Huang, M. S. Jiang, and H. Jiang, “Contrast agents for photoacoustic and thermoacoustic imaging: a review,” Int. J. Mol. Sci. 15, 23616–23639 (2014).
[Crossref]

Kaberniuk, A. A.

J. Yao, A. A. Kaberniuk, L. Li, D. M. Shcherbakova, R. Zhang, L. Wang, G. Li, V. V. Verkhusha, and L. V. Wang, “Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe,” Nat. Methods 13, 67–73 (2016).
[Crossref]

Kennedy, M. J.

Kolios, M. C.

E. M. Strohm, M. J. Moore, and M. C. Kolios, “Single cell photoacoustic microscopy: a review,” IEEE J. Sel. Top. Quantum Electron. 22, 137–151 (2016).
[Crossref]

Li, C.

Li, G.

J. Yao, A. A. Kaberniuk, L. Li, D. M. Shcherbakova, R. Zhang, L. Wang, G. Li, V. V. Verkhusha, and L. V. Wang, “Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe,” Nat. Methods 13, 67–73 (2016).
[Crossref]

Li, L.

J. Yao, A. A. Kaberniuk, L. Li, D. M. Shcherbakova, R. Zhang, L. Wang, G. Li, V. V. Verkhusha, and L. V. Wang, “Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe,” Nat. Methods 13, 67–73 (2016).
[Crossref]

Y. He, L. Wang, J. Shi, J. Yao, L. Li, R. Zhang, C.-H. Huang, J. Zou, and L. V. Wang, “In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells,” Sci. Rep. 6, 39616 (2016).
[Crossref]

J. Yao, L. Wang, J. M. K. Yang, K. I. Maslov, T. T. Wong, L. Li, C.-H. Huang, J. Zuo, and L. V. Wang, “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods 12, 407–410 (2015).
[Crossref]

L. Li, C. Yeh, S. Hu, L. Wang, B. T. Soetikno, R. Chen, Q. Zhou, K. K. Shung, K. I. Maslov, and L. V. Wang, “Fully motorized optical-resolution photoacoustic microscopy,” Opt. Lett. 39, 2117–2120 (2014).
[Crossref]

Linsenmeier, R. A.

J. Yi, W. Liu, S. Chen, V. Backman, N. Sheibani, C. M. Sorenson, A. A. Fawzi, R. A. Linsenmeier, and H. F. Zhang, “Visible light optical coherence tomography measures retinal oxygen metabolic response to systemic oxygenation,” Light Sci. Appl. 4, e334 (2015).
[Crossref]

Liu, W.

J. Yi, W. Liu, S. Chen, V. Backman, N. Sheibani, C. M. Sorenson, A. A. Fawzi, R. A. Linsenmeier, and H. F. Zhang, “Visible light optical coherence tomography measures retinal oxygen metabolic response to systemic oxygenation,” Light Sci. Appl. 4, e334 (2015).
[Crossref]

Maslov, K.

L. Wang, K. Maslov, and L. V. Wang, “Single-cell label-free photoacoustic flowoxigraphy in vivo,” Proc. Natl. Acad. Sci. USA 110, 5759–5764 (2013).
[Crossref]

J. Yang, C. Favazza, R. Chen, J. Yao, S. Cai, K. Maslov, Q. Zhou, K. Shung, and L. Wang, “Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo,” Nat. Med. 18, 1297–1302 (2012).
[Crossref]

S. Hu, K. Maslov, and L. V. Wang, “Second-generation optical-resolution photoacoustic microscopy with improved sensitivity and speed,” Opt. Lett. 36, 1134–1136 (2011).
[Crossref]

K. Maslov, H. F. Zhang, S. Hu, and L. V. Wang, “Optical-resolution photoacoustic microscopy for in vivo imaging of single capillaries,” Opt. Lett. 33, 929–931 (2008).
[Crossref]

H. F. Zhang, K. Maslov, G. Stoica, and L. V. Wang, “Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging,” Nat. Biotechnol. 24, 848–851 (2006).
[Crossref]

Maslov, K. I.

J. Yao, L. Wang, J. M. K. Yang, K. I. Maslov, T. T. Wong, L. Li, C.-H. Huang, J. Zuo, and L. V. Wang, “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods 12, 407–410 (2015).
[Crossref]

P. Hai, J. Yao, K. I. Maslov, Y. Zhou, and L. V. Wang, “Near-infrared optical-resolution photoacoustic microscopy,” Opt. Lett. 39, 5192–5195 (2014).
[Crossref]

L. Li, C. Yeh, S. Hu, L. Wang, B. T. Soetikno, R. Chen, Q. Zhou, K. K. Shung, K. I. Maslov, and L. V. Wang, “Fully motorized optical-resolution photoacoustic microscopy,” Opt. Lett. 39, 2117–2120 (2014).
[Crossref]

S. Hu, K. I. Maslov, V. Tsytsarev, and L. V. Wang, “Functional transcranial brain imaging by optical-resolution photoacoustic microscopy,” J. Biomed. Opt. 14, 040503 (2009).
[Crossref]

Monchalin, J.-P.

G. Rousseau, B. Gauthier, A. Blouin, and J.-P. Monchalin, “Non-contact biomedical photoacoustic and ultrasound imaging,” J. Biomed. Opt. 17, 061217 (2012).
[Crossref]

G. Rousseau, A. Blouin, and J.-P. Monchalin, “Non-contact photoacoustic tomography and ultrasonography for tissue imaging,” Biomed. Opt. Express 3, 16–25 (2012).
[Crossref]

Moore, M. J.

E. M. Strohm, M. J. Moore, and M. C. Kolios, “Single cell photoacoustic microscopy: a review,” IEEE J. Sel. Top. Quantum Electron. 22, 137–151 (2016).
[Crossref]

Niessen, W. J.

A. F. Frangi, W. J. Niessen, K. L. Vincken, and M. A. Viergever, Medical Image Computing and Computer-Assisted Intervention — MICCAI’98: First International Conference Cambridge, MA, USA, October 11–13, 1998 Proceedings, W. M. Wells, A. Colchester, and S. Delp, eds. (Springer, 1998), pp. 130–137.

Ning, B.

Nuster, R.

Paltauf, G.

Paproski, R.

P. Hajireza, W. Shi, K. Bell, R. Paproski, and R. Zemp, “Non-interferometric photoacoustic remote sensing microscopy,” Light Sci. Appl. 6, e16278 (2017).
[Crossref]

Paproski, R. J.

R. J. Paproski, A. Heinmiller, K. Wachowicz, and R. J. Zemp, “Multi-wavelength photoacoustic imaging of inducible tyrosinase reporter gene expression in xenograft tumors,” Sci. Rep. 4, 5329 (2014).
[Crossref]

Reza, P.

L. Snider, K. Bell, P. Reza, and R. J. Zemp, “Toward wide-field high-speed photoacoustic remote sensing microscopy,” Proc. SPIE 10494, 1049423 (2018).
[Crossref]

Rousseau, G.

G. Rousseau, B. Gauthier, A. Blouin, and J.-P. Monchalin, “Non-contact biomedical photoacoustic and ultrasound imaging,” J. Biomed. Opt. 17, 061217 (2012).
[Crossref]

G. Rousseau, A. Blouin, and J.-P. Monchalin, “Non-contact photoacoustic tomography and ultrasonography for tissue imaging,” Biomed. Opt. Express 3, 16–25 (2012).
[Crossref]

Shcherbakova, D. M.

J. Yao, A. A. Kaberniuk, L. Li, D. M. Shcherbakova, R. Zhang, L. Wang, G. Li, V. V. Verkhusha, and L. V. Wang, “Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe,” Nat. Methods 13, 67–73 (2016).
[Crossref]

Sheibani, N.

J. Yi, W. Liu, S. Chen, V. Backman, N. Sheibani, C. M. Sorenson, A. A. Fawzi, R. A. Linsenmeier, and H. F. Zhang, “Visible light optical coherence tomography measures retinal oxygen metabolic response to systemic oxygenation,” Light Sci. Appl. 4, e334 (2015).
[Crossref]

Shi, J.

Y. He, L. Wang, J. Shi, J. Yao, L. Li, R. Zhang, C.-H. Huang, J. Zou, and L. V. Wang, “In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells,” Sci. Rep. 6, 39616 (2016).
[Crossref]

Shi, P.

Shi, W.

P. Hajireza, W. Shi, K. Bell, R. Paproski, and R. Zemp, “Non-interferometric photoacoustic remote sensing microscopy,” Light Sci. Appl. 6, e16278 (2017).
[Crossref]

P. Hajireza, W. Shi, and R. Zemp, “Label-free in vivo GRIN-lens optical resolution photoacoustic micro-endoscopy,” Laser Phys. Lett. 10, 055603 (2013).
[Crossref]

P. Hajireza, W. Shi, and R. J. Zemp, “Label-free in vivo fiber-based optical-resolution photoacoustic microscopy,” Opt. Lett. 36, 4107–4109 (2011).
[Crossref]

P. Hajireza, W. Shi, and R. J. Zemp, “Real-time handheld optical-resolution photoacoustic microscopy,” Opt. Express 19, 20097–20102 (2011).
[Crossref]

Shung, K.

J. Yang, C. Favazza, R. Chen, J. Yao, S. Cai, K. Maslov, Q. Zhou, K. Shung, and L. Wang, “Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo,” Nat. Med. 18, 1297–1302 (2012).
[Crossref]

Shung, K. K.

Slezak, P.

Snider, L.

L. Snider, K. Bell, P. Reza, and R. J. Zemp, “Toward wide-field high-speed photoacoustic remote sensing microscopy,” Proc. SPIE 10494, 1049423 (2018).
[Crossref]

Soetikno, B. T.

Sorenson, C. M.

J. Yi, W. Liu, S. Chen, V. Backman, N. Sheibani, C. M. Sorenson, A. A. Fawzi, R. A. Linsenmeier, and H. F. Zhang, “Visible light optical coherence tomography measures retinal oxygen metabolic response to systemic oxygenation,” Light Sci. Appl. 4, e334 (2015).
[Crossref]

Sorge, J.

Stoica, G.

H. F. Zhang, K. Maslov, G. Stoica, and L. V. Wang, “Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging,” Nat. Biotechnol. 24, 848–851 (2006).
[Crossref]

Strohm, E. M.

E. M. Strohm, M. J. Moore, and M. C. Kolios, “Single cell photoacoustic microscopy: a review,” IEEE J. Sel. Top. Quantum Electron. 22, 137–151 (2016).
[Crossref]

Sun, N.

Tsytsarev, V.

S. Hu, K. I. Maslov, V. Tsytsarev, and L. V. Wang, “Functional transcranial brain imaging by optical-resolution photoacoustic microscopy,” J. Biomed. Opt. 14, 040503 (2009).
[Crossref]

Venugopalan, V.

S. A. Carp and V. Venugopalan, “Optoacoustic imaging based on the interferometric measurement of surface displacement,” J. Biomed. Opt. 12, 064001 (2007).
[Crossref]

Verkhusha, V. V.

J. Yao, A. A. Kaberniuk, L. Li, D. M. Shcherbakova, R. Zhang, L. Wang, G. Li, V. V. Verkhusha, and L. V. Wang, “Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe,” Nat. Methods 13, 67–73 (2016).
[Crossref]

Viergever, M. A.

A. F. Frangi, W. J. Niessen, K. L. Vincken, and M. A. Viergever, Medical Image Computing and Computer-Assisted Intervention — MICCAI’98: First International Conference Cambridge, MA, USA, October 11–13, 1998 Proceedings, W. M. Wells, A. Colchester, and S. Delp, eds. (Springer, 1998), pp. 130–137.

Vincken, K. L.

A. F. Frangi, W. J. Niessen, K. L. Vincken, and M. A. Viergever, Medical Image Computing and Computer-Assisted Intervention — MICCAI’98: First International Conference Cambridge, MA, USA, October 11–13, 1998 Proceedings, W. M. Wells, A. Colchester, and S. Delp, eds. (Springer, 1998), pp. 130–137.

Wachowicz, K.

R. J. Paproski, A. Heinmiller, K. Wachowicz, and R. J. Zemp, “Multi-wavelength photoacoustic imaging of inducible tyrosinase reporter gene expression in xenograft tumors,” Sci. Rep. 4, 5329 (2014).
[Crossref]

Wang, L.

J. Yao, A. A. Kaberniuk, L. Li, D. M. Shcherbakova, R. Zhang, L. Wang, G. Li, V. V. Verkhusha, and L. V. Wang, “Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe,” Nat. Methods 13, 67–73 (2016).
[Crossref]

Y. He, L. Wang, J. Shi, J. Yao, L. Li, R. Zhang, C.-H. Huang, J. Zou, and L. V. Wang, “In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells,” Sci. Rep. 6, 39616 (2016).
[Crossref]

J. Yao, L. Wang, J. M. K. Yang, K. I. Maslov, T. T. Wong, L. Li, C.-H. Huang, J. Zuo, and L. V. Wang, “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods 12, 407–410 (2015).
[Crossref]

L. Li, C. Yeh, S. Hu, L. Wang, B. T. Soetikno, R. Chen, Q. Zhou, K. K. Shung, K. I. Maslov, and L. V. Wang, “Fully motorized optical-resolution photoacoustic microscopy,” Opt. Lett. 39, 2117–2120 (2014).
[Crossref]

L. Wang, K. Maslov, and L. V. Wang, “Single-cell label-free photoacoustic flowoxigraphy in vivo,” Proc. Natl. Acad. Sci. USA 110, 5759–5764 (2013).
[Crossref]

J. Yang, C. Favazza, R. Chen, J. Yao, S. Cai, K. Maslov, Q. Zhou, K. Shung, and L. Wang, “Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo,” Nat. Med. 18, 1297–1302 (2012).
[Crossref]

Wang, L. V.

J. Yao, A. A. Kaberniuk, L. Li, D. M. Shcherbakova, R. Zhang, L. Wang, G. Li, V. V. Verkhusha, and L. V. Wang, “Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe,” Nat. Methods 13, 67–73 (2016).
[Crossref]

Y. He, L. Wang, J. Shi, J. Yao, L. Li, R. Zhang, C.-H. Huang, J. Zou, and L. V. Wang, “In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells,” Sci. Rep. 6, 39616 (2016).
[Crossref]

J. Yao, L. Wang, J. M. K. Yang, K. I. Maslov, T. T. Wong, L. Li, C.-H. Huang, J. Zuo, and L. V. Wang, “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods 12, 407–410 (2015).
[Crossref]

L. V. Wang and L. Gao, “Photoacoustic microscopy and computed tomography: from bench to bedside,” Annu. Rev. Biomed. Eng. 16, 155–185 (2014).
[Crossref]

P. Hai, J. Yao, K. I. Maslov, Y. Zhou, and L. V. Wang, “Near-infrared optical-resolution photoacoustic microscopy,” Opt. Lett. 39, 5192–5195 (2014).
[Crossref]

L. Li, C. Yeh, S. Hu, L. Wang, B. T. Soetikno, R. Chen, Q. Zhou, K. K. Shung, K. I. Maslov, and L. V. Wang, “Fully motorized optical-resolution photoacoustic microscopy,” Opt. Lett. 39, 2117–2120 (2014).
[Crossref]

L. Wang, K. Maslov, and L. V. Wang, “Single-cell label-free photoacoustic flowoxigraphy in vivo,” Proc. Natl. Acad. Sci. USA 110, 5759–5764 (2013).
[Crossref]

S. Hu, K. Maslov, and L. V. Wang, “Second-generation optical-resolution photoacoustic microscopy with improved sensitivity and speed,” Opt. Lett. 36, 1134–1136 (2011).
[Crossref]

L. V. Wang, “Multiscale photoacoustic microscopy and computed tomography,” Nat. Photonics 3, 503–509 (2009).
[Crossref]

S. Hu, K. I. Maslov, V. Tsytsarev, and L. V. Wang, “Functional transcranial brain imaging by optical-resolution photoacoustic microscopy,” J. Biomed. Opt. 14, 040503 (2009).
[Crossref]

K. Maslov, H. F. Zhang, S. Hu, and L. V. Wang, “Optical-resolution photoacoustic microscopy for in vivo imaging of single capillaries,” Opt. Lett. 33, 929–931 (2008).
[Crossref]

H. F. Zhang, K. Maslov, G. Stoica, and L. V. Wang, “Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging,” Nat. Biotechnol. 24, 848–851 (2006).
[Crossref]

Wang, R. K.

Wang, Y.

Z. Chen, S. Yang, Y. Wang, and D. Xing, “Noncontact broadband all-optical photoacoustic microscopy based on a low-coherence interferometer,” Appl. Phys. Lett. 106, 043701 (2015).
[Crossref]

Y. Wang, C. Li, and R. K. Wang, “Noncontact photoacoustic imaging achieved by using a low-coherence interferometer as the acoustic detector,” Opt. Lett. 36, 3975–3977 (2011).
[Crossref]

Wong, T. T.

J. Yao, L. Wang, J. M. K. Yang, K. I. Maslov, T. T. Wong, L. Li, C.-H. Huang, J. Zuo, and L. V. Wang, “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods 12, 407–410 (2015).
[Crossref]

Wu, D.

D. Wu, L. Huang, M. S. Jiang, and H. Jiang, “Contrast agents for photoacoustic and thermoacoustic imaging: a review,” Int. J. Mol. Sci. 15, 23616–23639 (2014).
[Crossref]

Xing, D.

Z. Chen, S. Yang, Y. Wang, and D. Xing, “Noncontact broadband all-optical photoacoustic microscopy based on a low-coherence interferometer,” Appl. Phys. Lett. 106, 043701 (2015).
[Crossref]

Yang, J.

J. Yang, C. Favazza, R. Chen, J. Yao, S. Cai, K. Maslov, Q. Zhou, K. Shung, and L. Wang, “Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo,” Nat. Med. 18, 1297–1302 (2012).
[Crossref]

Yang, J. M. K.

J. Yao, L. Wang, J. M. K. Yang, K. I. Maslov, T. T. Wong, L. Li, C.-H. Huang, J. Zuo, and L. V. Wang, “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods 12, 407–410 (2015).
[Crossref]

Yang, S.

Z. Chen, S. Yang, Y. Wang, and D. Xing, “Noncontact broadband all-optical photoacoustic microscopy based on a low-coherence interferometer,” Appl. Phys. Lett. 106, 043701 (2015).
[Crossref]

Yao, J.

J. Yao, “When pressure meets light: detecting the photoacoustic effect at the origin,” Light Sci. Appl. 6, e17062 (2017).
[Crossref]

J. Yao, A. A. Kaberniuk, L. Li, D. M. Shcherbakova, R. Zhang, L. Wang, G. Li, V. V. Verkhusha, and L. V. Wang, “Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe,” Nat. Methods 13, 67–73 (2016).
[Crossref]

Y. He, L. Wang, J. Shi, J. Yao, L. Li, R. Zhang, C.-H. Huang, J. Zou, and L. V. Wang, “In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells,” Sci. Rep. 6, 39616 (2016).
[Crossref]

J. Yao, L. Wang, J. M. K. Yang, K. I. Maslov, T. T. Wong, L. Li, C.-H. Huang, J. Zuo, and L. V. Wang, “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods 12, 407–410 (2015).
[Crossref]

P. Hai, J. Yao, K. I. Maslov, Y. Zhou, and L. V. Wang, “Near-infrared optical-resolution photoacoustic microscopy,” Opt. Lett. 39, 5192–5195 (2014).
[Crossref]

J. Yang, C. Favazza, R. Chen, J. Yao, S. Cai, K. Maslov, Q. Zhou, K. Shung, and L. Wang, “Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo,” Nat. Med. 18, 1297–1302 (2012).
[Crossref]

Yeh, C.

Yi, J.

J. Yi, W. Liu, S. Chen, V. Backman, N. Sheibani, C. M. Sorenson, A. A. Fawzi, R. A. Linsenmeier, and H. F. Zhang, “Visible light optical coherence tomography measures retinal oxygen metabolic response to systemic oxygenation,” Light Sci. Appl. 4, e334 (2015).
[Crossref]

Zamiri, S.

Zemp, R.

Zemp, R. J.

Zhang, H. F.

J. Yi, W. Liu, S. Chen, V. Backman, N. Sheibani, C. M. Sorenson, A. A. Fawzi, R. A. Linsenmeier, and H. F. Zhang, “Visible light optical coherence tomography measures retinal oxygen metabolic response to systemic oxygenation,” Light Sci. Appl. 4, e334 (2015).
[Crossref]

K. Maslov, H. F. Zhang, S. Hu, and L. V. Wang, “Optical-resolution photoacoustic microscopy for in vivo imaging of single capillaries,” Opt. Lett. 33, 929–931 (2008).
[Crossref]

H. F. Zhang, K. Maslov, G. Stoica, and L. V. Wang, “Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging,” Nat. Biotechnol. 24, 848–851 (2006).
[Crossref]

Zhang, R.

J. Yao, A. A. Kaberniuk, L. Li, D. M. Shcherbakova, R. Zhang, L. Wang, G. Li, V. V. Verkhusha, and L. V. Wang, “Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe,” Nat. Methods 13, 67–73 (2016).
[Crossref]

Y. He, L. Wang, J. Shi, J. Yao, L. Li, R. Zhang, C.-H. Huang, J. Zou, and L. V. Wang, “In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells,” Sci. Rep. 6, 39616 (2016).
[Crossref]

Zhou, Q.

Zhou, Y.

Zou, J.

Y. He, L. Wang, J. Shi, J. Yao, L. Li, R. Zhang, C.-H. Huang, J. Zou, and L. V. Wang, “In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells,” Sci. Rep. 6, 39616 (2016).
[Crossref]

Zuo, J.

J. Yao, L. Wang, J. M. K. Yang, K. I. Maslov, T. T. Wong, L. Li, C.-H. Huang, J. Zuo, and L. V. Wang, “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods 12, 407–410 (2015).
[Crossref]

Annu. Rev. Biomed. Eng. (1)

L. V. Wang and L. Gao, “Photoacoustic microscopy and computed tomography: from bench to bedside,” Annu. Rev. Biomed. Eng. 16, 155–185 (2014).
[Crossref]

Appl. Opt. (2)

Appl. Phys. Lett. (1)

Z. Chen, S. Yang, Y. Wang, and D. Xing, “Noncontact broadband all-optical photoacoustic microscopy based on a low-coherence interferometer,” Appl. Phys. Lett. 106, 043701 (2015).
[Crossref]

Biomed. Opt. Express (4)

IEEE J. Sel. Top. Quantum Electron. (1)

E. M. Strohm, M. J. Moore, and M. C. Kolios, “Single cell photoacoustic microscopy: a review,” IEEE J. Sel. Top. Quantum Electron. 22, 137–151 (2016).
[Crossref]

Int. J. Mol. Sci. (1)

D. Wu, L. Huang, M. S. Jiang, and H. Jiang, “Contrast agents for photoacoustic and thermoacoustic imaging: a review,” Int. J. Mol. Sci. 15, 23616–23639 (2014).
[Crossref]

Interface Focus (1)

P. Beard, “Biomedical photoacoustic imaging,” Interface Focus 1, 602–631 (2011).
[Crossref]

J. Biomed. Opt. (3)

S. Hu, K. I. Maslov, V. Tsytsarev, and L. V. Wang, “Functional transcranial brain imaging by optical-resolution photoacoustic microscopy,” J. Biomed. Opt. 14, 040503 (2009).
[Crossref]

G. Rousseau, B. Gauthier, A. Blouin, and J.-P. Monchalin, “Non-contact biomedical photoacoustic and ultrasound imaging,” J. Biomed. Opt. 17, 061217 (2012).
[Crossref]

S. A. Carp and V. Venugopalan, “Optoacoustic imaging based on the interferometric measurement of surface displacement,” J. Biomed. Opt. 12, 064001 (2007).
[Crossref]

Laser Phys. Lett. (1)

P. Hajireza, W. Shi, and R. Zemp, “Label-free in vivo GRIN-lens optical resolution photoacoustic micro-endoscopy,” Laser Phys. Lett. 10, 055603 (2013).
[Crossref]

Light Sci. Appl. (3)

P. Hajireza, W. Shi, K. Bell, R. Paproski, and R. Zemp, “Non-interferometric photoacoustic remote sensing microscopy,” Light Sci. Appl. 6, e16278 (2017).
[Crossref]

J. Yi, W. Liu, S. Chen, V. Backman, N. Sheibani, C. M. Sorenson, A. A. Fawzi, R. A. Linsenmeier, and H. F. Zhang, “Visible light optical coherence tomography measures retinal oxygen metabolic response to systemic oxygenation,” Light Sci. Appl. 4, e334 (2015).
[Crossref]

J. Yao, “When pressure meets light: detecting the photoacoustic effect at the origin,” Light Sci. Appl. 6, e17062 (2017).
[Crossref]

Nat. Biotechnol. (1)

H. F. Zhang, K. Maslov, G. Stoica, and L. V. Wang, “Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging,” Nat. Biotechnol. 24, 848–851 (2006).
[Crossref]

Nat. Med. (1)

J. Yang, C. Favazza, R. Chen, J. Yao, S. Cai, K. Maslov, Q. Zhou, K. Shung, and L. Wang, “Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo,” Nat. Med. 18, 1297–1302 (2012).
[Crossref]

Nat. Methods (2)

J. Yao, L. Wang, J. M. K. Yang, K. I. Maslov, T. T. Wong, L. Li, C.-H. Huang, J. Zuo, and L. V. Wang, “High-speed label-free functional photoacoustic microscopy of mouse brain in action,” Nat. Methods 12, 407–410 (2015).
[Crossref]

J. Yao, A. A. Kaberniuk, L. Li, D. M. Shcherbakova, R. Zhang, L. Wang, G. Li, V. V. Verkhusha, and L. V. Wang, “Multiscale photoacoustic tomography using reversibly switchable bacterial phytochrome as a near-infrared photochromic probe,” Nat. Methods 13, 67–73 (2016).
[Crossref]

Nat. Photonics (1)

L. V. Wang, “Multiscale photoacoustic microscopy and computed tomography,” Nat. Photonics 3, 503–509 (2009).
[Crossref]

Opt. Express (1)

Opt. Lett. (11)

K. Maslov, H. F. Zhang, S. Hu, and L. V. Wang, “Optical-resolution photoacoustic microscopy for in vivo imaging of single capillaries,” Opt. Lett. 33, 929–931 (2008).
[Crossref]

P. Hajireza, W. Shi, and R. J. Zemp, “Label-free in vivo fiber-based optical-resolution photoacoustic microscopy,” Opt. Lett. 36, 4107–4109 (2011).
[Crossref]

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Proc. Natl. Acad. Sci. USA (1)

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Supplementary Material (1)

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Figures (4)

Fig. 1.
Fig. 1. dPARS mechanism. (a) PARS versus OR-PAM detection mechanism. PARS technology, unlike any other photoacoustic imaging systems, does not measure propagated ultrasound pressures but rather the initial pressure generated at the origin. (b) Comparison between two different PARS modes, a deep penetrating mode and a high-resolution mode. RBC: red blood cell. l t , Excitation = transport mean-free path of the excitation beam. l t , Probe = transport mean-free path of the probe beam.
Fig. 2.
Fig. 2. dPARS experimental setup and validation. (a) Simplified PARS apparatus. The fundamental 532-nm pulsed excitation beam is fed into a polarization-maintaining single-mode fiber (SMF), which can generate stimulated Raman scattering (SRS) broadening in the spectrum. The 1310-nm probe beam is split into the primary component made to be co-aligned with the excitation. The two beams are then co-scanned using a galvanometer mirror system or may be held stationary while scanning of the sample is performed with a motor stage (MS). The back-reflected probe beam is fed into one side of a balanced photodiode (BPD) and is compared with the smaller component of the original probe beam for balanced detection. Other system components: collimator (C), polarized beam splitter (PBS), beam splitter (BS), beam combiner (BC), attenuator (A), quarter wave plate (QWP), objective lens (OL), lens (L). (b) Image of carbon fiber networks using the deep penetrating imaging mode. (c) Image of carbon fiber networks using the high-resolution imaging mode, as well as an inset image of 100-nm gold nanoparticles. (d) Images of carbon fiber networks at various depths in tissue-mimicking solution.
Fig. 3.
Fig. 3. In vivo PARS microscopy structural images. (a) Image of en face microvasculature in the ear of an 8-week-old nude mouse (NU/NU, Charles River, MA, USA) using the high-resolution mode (scale bar: 500 µm) (b) In vivo image of red blood cells in the mouse ear using the high-resolution mode (scale bar: 5 µm) (c) Image of mouse ear vasculature using the deep-penetrating mode (scale bar: 500 µm) (d) Image of en face microvasculature in the tip of a mouse ear (NU/NU, Charles River, MA, USA) using the high-resolution mode (scale bar: 500 µm) (e) Images of back flank of mouse at various depths using the deep-penetrating mode (scale bar: 100 µm).
Fig. 4.
Fig. 4. Functional images SO 2 measurement of en face microvasculature in the ear of an 8-week-old nude mouse (NU/NU, Charles River, MA, USA).

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