Abstract

We suggest a new implementation for rapid reconstruction of three-dimensional (3-D) refractive index (RI) maps of biological cells acquired by tomographic phase microscopy (TPM). The TPM computational reconstruction process is extremely time consuming, making the analysis of large data sets unreasonably slow and the real-time 3-D visualization of the results impossible. Our implementation uses new phase extraction, phase unwrapping and Fourier slice algorithms, suitable for efficient CPU or GPU implementations. The experimental setup includes an external off-axis interferometric module connected to an inverted microscope illuminated coherently. We used single cell rotation by micro-manipulation to obtain interferometric projections from 73 viewing angles over a 180° angular range. Our parallel algorithms were implemented using Nvidia's CUDA C platform, running on Nvidia's Tesla K20c GPU. This implementation yields, for the first time to our knowledge, a 3-D reconstruction rate higher than video rate of 25 frames per second for 256 × 256-pixel interferograms with 73 different projection angles (64 × 64 × 64 output). This allows us to calculate additional cellular parameters, while still processing faster than video rate. This technique is expected to find uses for real-time 3-D cell visualization and processing, while yielding fast feedback for medical diagnosis and cell sorting.

© 2016 Optical Society of America

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2016 (1)

2015 (5)

2014 (2)

P. Girshovitz and N. T. Shaked, “Real-time quantitative phase reconstruction in off-axis digital holography using multiplexing,” Opt. Lett. 39(8), 2262–2265 (2014).
[Crossref] [PubMed]

M. Birk, M. Zapf, M. Balzer, N. Ruiter, and J. Becker, “A comprehensive comparison of GPU-and FPGA-based acceleration of reflection image reconstruction for 3D ultrasound computer tomography,” J. Real-Time. Image. Proc. 9(1), 159–170 (2014).

2013 (5)

E. Kretzek, M. Zapf, M. Birk, H. Gemmeke, and N. V. Ruiter, “GPU based acceleration of 3D USCT image reconstruction with efficient integration into MATLAB,” Proc. SPIE 8675, 86750O (2013).
[Crossref]

A. V. Goncharsky and S. Y. Romanov, “Supercomputer technologies in inverse problems of ultrasound tomography,” Inverse Probl. 29(7), 075004 (2013).
[Crossref]

K. Kim, H. Yoon, M. Diez-Silva, M. Dao, R. R. Dasari, and Y. Park, “High-resolution three-dimensional imaging of red blood cells parasitized by Plasmodium falciparum and in situ hemozoin crystals using optical diffraction tomography,” J. Biomed. Opt. 19(1), 011005 (2013).
[Crossref] [PubMed]

K. Kim, K. S. Kim, H. Park, J. C. Ye, and Y. Park, “Real-time visualization of 3-D dynamic microscopic objects using optical diffraction tomography,” Opt. Express 21(26), 32269–32278 (2013).
[Crossref] [PubMed]

P. Girshovitz and N. T. Shaked, “Compact and portable low-coherence interferometer with off-axis geometry for quantitative phase microscopy and nanoscopy,” Opt. Express 21(5), 5701–5714 (2013).
[Crossref] [PubMed]

2012 (2)

N. T. Shaked, “Quantitative phase microscopy of biological samples using a portable interferometer,” Opt. Lett. 37(11), 2016–2018 (2012).
[Crossref] [PubMed]

J. Bailleul, B. Simon, M. Debailleul, H. Liu, and O. Haeberlé, “GPU acceleration towards real-time image reconstruction in 3D tomographic diffractive microscopy,” Proc. SPIE 8437, 843707 (2012).
[Crossref]

2011 (1)

2010 (3)

F. R. N. C. Maia, A. MacDowell, S. Marchesini, H. A. Padmore, D. Y. Parkinson, J. Pien, A. Schirotzek, and C. Yang, “Compressive Phase Contrast Tomography,” Proc. SPIE 7800, 78000F (2010).
[Crossref]

Y. Okitsu, F. Ino, and K. Hagihara, “High-performance cone beam reconstruction using CUDA compatible GPUs,” Parallel Comput. 36(2), 129–141 (2010).
[Crossref]

P. B. Noël, A. M. Walczak, J. Xu, J. J. Corso, K. R. Hoffmann, and S. Schafer, “GPU-based cone beam computed tomography,” Comput. Methods Programs Biomed. 98(3), 271–277 (2010).
[Crossref] [PubMed]

2009 (1)

2008 (1)

N. Gac, S. Mancini, M. Desvignes, and D. Houzet, “High speed 3D tomography on CPU, GPU, and FPGA,” EURASIP J. Embed. Syst. 2008(1), 930250 (2008).
[Crossref]

2007 (2)

W. Choi, C. Fang-Yen, K. Badizadegan, S. Oh, N. Lue, R. R. Dasari, and M. S. Feld, “Tomographic phase microscopy,” Nat. Methods 4(9), 717–719 (2007).
[Crossref] [PubMed]

D. Castaño Díez, H. Mueller, and A. S. Frangakis, “Implementation and performance evaluation of reconstruction algorithms on graphics processors,” J. Struct. Biol. 157(1), 288–295 (2007).
[Crossref] [PubMed]

2006 (1)

2004 (1)

J. J. Fernández, J. M. Carazo, and I. García, “Three-dimensional reconstruction of cellular structures by electron microscope tomography and parallel computing,” J. Parallel Distrib. Comput. 64(2), 285–300 (2004).
[Crossref]

1981 (1)

R. G. Keys, “Cubic convolution interpolation for digital image processing,” IEEE Trans. Acoust. Speech Signal Process. 29(6), 1153–1160 (1981).
[Crossref]

Anssari, N.

J. Stratton, N. Anssari, C. Rodrigues, I. J. Sung, N. Obeid, L. Chang, G. D. Liu, and W. M. Hwu, “Optimization and architecture effects on GPU computing workload performance,” in Proceedings of IEEE conference on Innovative Parallel Computing (IEEE, 2012), pp. 1–10.
[Crossref]

Arroyo, M.

G. Ortega, J. Lobera, M. Arroyo, I. García, and E. M. Garzon, “High performance computing for optical diffraction tomography,” in Proceedings of IEEE conference on High Performance Computing and Simulation (IEEE, 2012), pp. 195–201.
[Crossref]

Backoach, O.

Badizadegan, K.

Y. Sung, W. Choi, C. Fang-Yen, K. Badizadegan, R. R. Dasari, and M. S. Feld, “Optical diffraction tomography for high resolution live cell imaging,” Opt. Express 17(1), 266–277 (2009).
[Crossref] [PubMed]

W. Choi, C. Fang-Yen, K. Badizadegan, S. Oh, N. Lue, R. R. Dasari, and M. S. Feld, “Tomographic phase microscopy,” Nat. Methods 4(9), 717–719 (2007).
[Crossref] [PubMed]

Bailleul, J.

J. Bailleul, B. Simon, M. Debailleul, H. Liu, and O. Haeberlé, “GPU acceleration towards real-time image reconstruction in 3D tomographic diffractive microscopy,” Proc. SPIE 8437, 843707 (2012).
[Crossref]

Balzer, M.

M. Birk, M. Zapf, M. Balzer, N. Ruiter, and J. Becker, “A comprehensive comparison of GPU-and FPGA-based acceleration of reflection image reconstruction for 3D ultrasound computer tomography,” J. Real-Time. Image. Proc. 9(1), 159–170 (2014).

Barbastathis, G.

N. Loomis, L. Waller, and G. Barbastathis, “High-speed phase recovery using chromatic transport of intensity computation in graphics processing units,” in Proc. Biomedical Optics and 3-D imaging (2010), paper JMA7.

Becker, J.

M. Birk, M. Zapf, M. Balzer, N. Ruiter, and J. Becker, “A comprehensive comparison of GPU-and FPGA-based acceleration of reflection image reconstruction for 3D ultrasound computer tomography,” J. Real-Time. Image. Proc. 9(1), 159–170 (2014).

Birk, M.

M. Birk, M. Zapf, M. Balzer, N. Ruiter, and J. Becker, “A comprehensive comparison of GPU-and FPGA-based acceleration of reflection image reconstruction for 3D ultrasound computer tomography,” J. Real-Time. Image. Proc. 9(1), 159–170 (2014).

E. Kretzek, M. Zapf, M. Birk, H. Gemmeke, and N. V. Ruiter, “GPU based acceleration of 3D USCT image reconstruction with efficient integration into MATLAB,” Proc. SPIE 8675, 86750O (2013).
[Crossref]

Carazo, J. M.

J. J. Fernández, J. M. Carazo, and I. García, “Three-dimensional reconstruction of cellular structures by electron microscope tomography and parallel computing,” J. Parallel Distrib. Comput. 64(2), 285–300 (2004).
[Crossref]

Castaño Díez, D.

D. Castaño Díez, H. Mueller, and A. S. Frangakis, “Implementation and performance evaluation of reconstruction algorithms on graphics processors,” J. Struct. Biol. 157(1), 288–295 (2007).
[Crossref] [PubMed]

Chang, L.

J. Stratton, N. Anssari, C. Rodrigues, I. J. Sung, N. Obeid, L. Chang, G. D. Liu, and W. M. Hwu, “Optimization and architecture effects on GPU computing workload performance,” in Proceedings of IEEE conference on Innovative Parallel Computing (IEEE, 2012), pp. 1–10.
[Crossref]

Charrière, F.

Chen, Y.

D. Xiao, Y. Chen, B. Qian, L. Yang, and Y. Kang, “Cone-beam computed tomography reconstruction accelerated with CUDA,” in Proceedings of IEEE conference on Biomedical Engineering and Informatics (IEEE, 2011), pp. 214–218.
[Crossref]

Choi, C.

Choi, W.

Y. Sung, W. Choi, C. Fang-Yen, K. Badizadegan, R. R. Dasari, and M. S. Feld, “Optical diffraction tomography for high resolution live cell imaging,” Opt. Express 17(1), 266–277 (2009).
[Crossref] [PubMed]

W. Choi, C. Fang-Yen, K. Badizadegan, S. Oh, N. Lue, R. R. Dasari, and M. S. Feld, “Tomographic phase microscopy,” Nat. Methods 4(9), 717–719 (2007).
[Crossref] [PubMed]

Colomb, T.

Coppola, G.

P. Memmolo, L. Miccio, M. Paturzo, G. Di Caprio, G. Coppola, P. A. Netti, and P. Ferraro, “Recent advances in holographic 3D particle tracking,” Adv. Opt. Photonics 7(4), 713–755 (2015).
[Crossref]

Corso, J. J.

P. B. Noël, A. M. Walczak, J. Xu, J. J. Corso, K. R. Hoffmann, and S. Schafer, “GPU-based cone beam computed tomography,” Comput. Methods Programs Biomed. 98(3), 271–277 (2010).
[Crossref] [PubMed]

Cuche, E.

Dao, M.

K. Kim, H. Yoon, M. Diez-Silva, M. Dao, R. R. Dasari, and Y. Park, “High-resolution three-dimensional imaging of red blood cells parasitized by Plasmodium falciparum and in situ hemozoin crystals using optical diffraction tomography,” J. Biomed. Opt. 19(1), 011005 (2013).
[Crossref] [PubMed]

Dasari, R. R.

K. Kim, H. Yoon, M. Diez-Silva, M. Dao, R. R. Dasari, and Y. Park, “High-resolution three-dimensional imaging of red blood cells parasitized by Plasmodium falciparum and in situ hemozoin crystals using optical diffraction tomography,” J. Biomed. Opt. 19(1), 011005 (2013).
[Crossref] [PubMed]

Y. Sung, W. Choi, C. Fang-Yen, K. Badizadegan, R. R. Dasari, and M. S. Feld, “Optical diffraction tomography for high resolution live cell imaging,” Opt. Express 17(1), 266–277 (2009).
[Crossref] [PubMed]

W. Choi, C. Fang-Yen, K. Badizadegan, S. Oh, N. Lue, R. R. Dasari, and M. S. Feld, “Tomographic phase microscopy,” Nat. Methods 4(9), 717–719 (2007).
[Crossref] [PubMed]

Debailleul, M.

J. Bailleul, B. Simon, M. Debailleul, H. Liu, and O. Haeberlé, “GPU acceleration towards real-time image reconstruction in 3D tomographic diffractive microscopy,” Proc. SPIE 8437, 843707 (2012).
[Crossref]

Depeursinge, C.

Desvignes, M.

N. Gac, S. Mancini, M. Desvignes, and D. Houzet, “High speed 3D tomography on CPU, GPU, and FPGA,” EURASIP J. Embed. Syst. 2008(1), 930250 (2008).
[Crossref]

Di Caprio, G.

P. Memmolo, L. Miccio, M. Paturzo, G. Di Caprio, G. Coppola, P. A. Netti, and P. Ferraro, “Recent advances in holographic 3D particle tracking,” Adv. Opt. Photonics 7(4), 713–755 (2015).
[Crossref]

Diez-Silva, M.

K. Kim, H. Yoon, M. Diez-Silva, M. Dao, R. R. Dasari, and Y. Park, “High-resolution three-dimensional imaging of red blood cells parasitized by Plasmodium falciparum and in situ hemozoin crystals using optical diffraction tomography,” J. Biomed. Opt. 19(1), 011005 (2013).
[Crossref] [PubMed]

Ding, H.

Do, M.

Fang-Yen, C.

Y. Sung, W. Choi, C. Fang-Yen, K. Badizadegan, R. R. Dasari, and M. S. Feld, “Optical diffraction tomography for high resolution live cell imaging,” Opt. Express 17(1), 266–277 (2009).
[Crossref] [PubMed]

W. Choi, C. Fang-Yen, K. Badizadegan, S. Oh, N. Lue, R. R. Dasari, and M. S. Feld, “Tomographic phase microscopy,” Nat. Methods 4(9), 717–719 (2007).
[Crossref] [PubMed]

Feld, M. S.

Y. Sung, W. Choi, C. Fang-Yen, K. Badizadegan, R. R. Dasari, and M. S. Feld, “Optical diffraction tomography for high resolution live cell imaging,” Opt. Express 17(1), 266–277 (2009).
[Crossref] [PubMed]

W. Choi, C. Fang-Yen, K. Badizadegan, S. Oh, N. Lue, R. R. Dasari, and M. S. Feld, “Tomographic phase microscopy,” Nat. Methods 4(9), 717–719 (2007).
[Crossref] [PubMed]

Fernández, J. J.

J. J. Fernández, J. M. Carazo, and I. García, “Three-dimensional reconstruction of cellular structures by electron microscope tomography and parallel computing,” J. Parallel Distrib. Comput. 64(2), 285–300 (2004).
[Crossref]

Ferraro, P.

P. Memmolo, L. Miccio, M. Paturzo, G. Di Caprio, G. Coppola, P. A. Netti, and P. Ferraro, “Recent advances in holographic 3D particle tracking,” Adv. Opt. Photonics 7(4), 713–755 (2015).
[Crossref]

Fessler, J. A.

M. G. McGaffin and J. A. Fessler, “Alternating dual updates algorithm for X-ray CT reconstruction on the GPU,” IEEE Trans Comput Imaging 1(3), 186–199 (2015).
[Crossref] [PubMed]

Frangakis, A. S.

D. Castaño Díez, H. Mueller, and A. S. Frangakis, “Implementation and performance evaluation of reconstruction algorithms on graphics processors,” J. Struct. Biol. 157(1), 288–295 (2007).
[Crossref] [PubMed]

Gac, N.

N. Gac, S. Mancini, M. Desvignes, and D. Houzet, “High speed 3D tomography on CPU, GPU, and FPGA,” EURASIP J. Embed. Syst. 2008(1), 930250 (2008).
[Crossref]

García, I.

J. J. Fernández, J. M. Carazo, and I. García, “Three-dimensional reconstruction of cellular structures by electron microscope tomography and parallel computing,” J. Parallel Distrib. Comput. 64(2), 285–300 (2004).
[Crossref]

G. Ortega, J. Lobera, M. Arroyo, I. García, and E. M. Garzon, “High performance computing for optical diffraction tomography,” in Proceedings of IEEE conference on High Performance Computing and Simulation (IEEE, 2012), pp. 195–201.
[Crossref]

Garzon, E. M.

G. Ortega, J. Lobera, M. Arroyo, I. García, and E. M. Garzon, “High performance computing for optical diffraction tomography,” in Proceedings of IEEE conference on High Performance Computing and Simulation (IEEE, 2012), pp. 195–201.
[Crossref]

Gemmeke, H.

E. Kretzek, M. Zapf, M. Birk, H. Gemmeke, and N. V. Ruiter, “GPU based acceleration of 3D USCT image reconstruction with efficient integration into MATLAB,” Proc. SPIE 8675, 86750O (2013).
[Crossref]

Gilboa, B.

Girshovitz, P.

Goncharsky, A. V.

A. V. Goncharsky and S. Y. Romanov, “Supercomputer technologies in inverse problems of ultrasound tomography,” Inverse Probl. 29(7), 075004 (2013).
[Crossref]

Habaza, M.

Haeberlé, O.

J. Bailleul, B. Simon, M. Debailleul, H. Liu, and O. Haeberlé, “GPU acceleration towards real-time image reconstruction in 3D tomographic diffractive microscopy,” Proc. SPIE 8437, 843707 (2012).
[Crossref]

Hagihara, K.

Y. Okitsu, F. Ino, and K. Hagihara, “High-performance cone beam reconstruction using CUDA compatible GPUs,” Parallel Comput. 36(2), 129–141 (2010).
[Crossref]

Hoffmann, K. R.

P. B. Noël, A. M. Walczak, J. Xu, J. J. Corso, K. R. Hoffmann, and S. Schafer, “GPU-based cone beam computed tomography,” Comput. Methods Programs Biomed. 98(3), 271–277 (2010).
[Crossref] [PubMed]

Hornegger, J.

H. Scherl, B. Keck, M. Kowarschik, and J. Hornegger, “Fast GPU-based CT reconstruction using the common unified device architecture (CUDA),” in Proceedings of IEEE conference on Nuclear Science (IEEE, 2007), pp. 4464–4466.
[Crossref]

Houzet, D.

N. Gac, S. Mancini, M. Desvignes, and D. Houzet, “High speed 3D tomography on CPU, GPU, and FPGA,” EURASIP J. Embed. Syst. 2008(1), 930250 (2008).
[Crossref]

Hwu, W. M.

J. Stratton, N. Anssari, C. Rodrigues, I. J. Sung, N. Obeid, L. Chang, G. D. Liu, and W. M. Hwu, “Optimization and architecture effects on GPU computing workload performance,” in Proceedings of IEEE conference on Innovative Parallel Computing (IEEE, 2012), pp. 1–10.
[Crossref]

Ino, F.

Y. Okitsu, F. Ino, and K. Hagihara, “High-performance cone beam reconstruction using CUDA compatible GPUs,” Parallel Comput. 36(2), 129–141 (2010).
[Crossref]

Jang, S.

Kang, Y.

D. Xiao, Y. Chen, B. Qian, L. Yang, and Y. Kang, “Cone-beam computed tomography reconstruction accelerated with CUDA,” in Proceedings of IEEE conference on Biomedical Engineering and Informatics (IEEE, 2011), pp. 214–218.
[Crossref]

Kariv, S.

Keck, B.

H. Scherl, B. Keck, M. Kowarschik, and J. Hornegger, “Fast GPU-based CT reconstruction using the common unified device architecture (CUDA),” in Proceedings of IEEE conference on Nuclear Science (IEEE, 2007), pp. 4464–4466.
[Crossref]

Keys, R. G.

R. G. Keys, “Cubic convolution interpolation for digital image processing,” IEEE Trans. Acoust. Speech Signal Process. 29(6), 1153–1160 (1981).
[Crossref]

Kim, K.

Kim, K. S.

Kowarschik, M.

H. Scherl, B. Keck, M. Kowarschik, and J. Hornegger, “Fast GPU-based CT reconstruction using the common unified device architecture (CUDA),” in Proceedings of IEEE conference on Nuclear Science (IEEE, 2007), pp. 4464–4466.
[Crossref]

Kretzek, E.

E. Kretzek, M. Zapf, M. Birk, H. Gemmeke, and N. V. Ruiter, “GPU based acceleration of 3D USCT image reconstruction with efficient integration into MATLAB,” Proc. SPIE 8675, 86750O (2013).
[Crossref]

Kuehn, J.

Liu, G. D.

J. Stratton, N. Anssari, C. Rodrigues, I. J. Sung, N. Obeid, L. Chang, G. D. Liu, and W. M. Hwu, “Optimization and architecture effects on GPU computing workload performance,” in Proceedings of IEEE conference on Innovative Parallel Computing (IEEE, 2012), pp. 1–10.
[Crossref]

Liu, H.

J. Bailleul, B. Simon, M. Debailleul, H. Liu, and O. Haeberlé, “GPU acceleration towards real-time image reconstruction in 3D tomographic diffractive microscopy,” Proc. SPIE 8437, 843707 (2012).
[Crossref]

Lobera, J.

G. Ortega, J. Lobera, M. Arroyo, I. García, and E. M. Garzon, “High performance computing for optical diffraction tomography,” in Proceedings of IEEE conference on High Performance Computing and Simulation (IEEE, 2012), pp. 195–201.
[Crossref]

Loomis, N.

N. Loomis, L. Waller, and G. Barbastathis, “High-speed phase recovery using chromatic transport of intensity computation in graphics processing units,” in Proc. Biomedical Optics and 3-D imaging (2010), paper JMA7.

Lue, N.

W. Choi, C. Fang-Yen, K. Badizadegan, S. Oh, N. Lue, R. R. Dasari, and M. S. Feld, “Tomographic phase microscopy,” Nat. Methods 4(9), 717–719 (2007).
[Crossref] [PubMed]

MacDowell, A.

F. R. N. C. Maia, A. MacDowell, S. Marchesini, H. A. Padmore, D. Y. Parkinson, J. Pien, A. Schirotzek, and C. Yang, “Compressive Phase Contrast Tomography,” Proc. SPIE 7800, 78000F (2010).
[Crossref]

Maia, F. R. N. C.

F. R. N. C. Maia, A. MacDowell, S. Marchesini, H. A. Padmore, D. Y. Parkinson, J. Pien, A. Schirotzek, and C. Yang, “Compressive Phase Contrast Tomography,” Proc. SPIE 7800, 78000F (2010).
[Crossref]

Mancini, S.

N. Gac, S. Mancini, M. Desvignes, and D. Houzet, “High speed 3D tomography on CPU, GPU, and FPGA,” EURASIP J. Embed. Syst. 2008(1), 930250 (2008).
[Crossref]

Marchesini, S.

F. R. N. C. Maia, A. MacDowell, S. Marchesini, H. A. Padmore, D. Y. Parkinson, J. Pien, A. Schirotzek, and C. Yang, “Compressive Phase Contrast Tomography,” Proc. SPIE 7800, 78000F (2010).
[Crossref]

Marian, A.

Marquet, P.

McGaffin, M. G.

M. G. McGaffin and J. A. Fessler, “Alternating dual updates algorithm for X-ray CT reconstruction on the GPU,” IEEE Trans Comput Imaging 1(3), 186–199 (2015).
[Crossref] [PubMed]

Memmolo, P.

P. Memmolo, L. Miccio, M. Paturzo, G. Di Caprio, G. Coppola, P. A. Netti, and P. Ferraro, “Recent advances in holographic 3D particle tracking,” Adv. Opt. Photonics 7(4), 713–755 (2015).
[Crossref]

Miccio, L.

P. Memmolo, L. Miccio, M. Paturzo, G. Di Caprio, G. Coppola, P. A. Netti, and P. Ferraro, “Recent advances in holographic 3D particle tracking,” Adv. Opt. Photonics 7(4), 713–755 (2015).
[Crossref]

Montfort, F.

Mueller, H.

D. Castaño Díez, H. Mueller, and A. S. Frangakis, “Implementation and performance evaluation of reconstruction algorithms on graphics processors,” J. Struct. Biol. 157(1), 288–295 (2007).
[Crossref] [PubMed]

Netti, P. A.

P. Memmolo, L. Miccio, M. Paturzo, G. Di Caprio, G. Coppola, P. A. Netti, and P. Ferraro, “Recent advances in holographic 3D particle tracking,” Adv. Opt. Photonics 7(4), 713–755 (2015).
[Crossref]

Noël, P. B.

P. B. Noël, A. M. Walczak, J. Xu, J. J. Corso, K. R. Hoffmann, and S. Schafer, “GPU-based cone beam computed tomography,” Comput. Methods Programs Biomed. 98(3), 271–277 (2010).
[Crossref] [PubMed]

Obeid, N.

J. Stratton, N. Anssari, C. Rodrigues, I. J. Sung, N. Obeid, L. Chang, G. D. Liu, and W. M. Hwu, “Optimization and architecture effects on GPU computing workload performance,” in Proceedings of IEEE conference on Innovative Parallel Computing (IEEE, 2012), pp. 1–10.
[Crossref]

Oh, S.

W. Choi, C. Fang-Yen, K. Badizadegan, S. Oh, N. Lue, R. R. Dasari, and M. S. Feld, “Tomographic phase microscopy,” Nat. Methods 4(9), 717–719 (2007).
[Crossref] [PubMed]

Okitsu, Y.

Y. Okitsu, F. Ino, and K. Hagihara, “High-performance cone beam reconstruction using CUDA compatible GPUs,” Parallel Comput. 36(2), 129–141 (2010).
[Crossref]

Ortega, G.

G. Ortega, J. Lobera, M. Arroyo, I. García, and E. M. Garzon, “High performance computing for optical diffraction tomography,” in Proceedings of IEEE conference on High Performance Computing and Simulation (IEEE, 2012), pp. 195–201.
[Crossref]

Padmore, H. A.

F. R. N. C. Maia, A. MacDowell, S. Marchesini, H. A. Padmore, D. Y. Parkinson, J. Pien, A. Schirotzek, and C. Yang, “Compressive Phase Contrast Tomography,” Proc. SPIE 7800, 78000F (2010).
[Crossref]

Park, H.

Park, Y.

Parkinson, D. Y.

F. R. N. C. Maia, A. MacDowell, S. Marchesini, H. A. Padmore, D. Y. Parkinson, J. Pien, A. Schirotzek, and C. Yang, “Compressive Phase Contrast Tomography,” Proc. SPIE 7800, 78000F (2010).
[Crossref]

Patel, S.

Paturzo, M.

P. Memmolo, L. Miccio, M. Paturzo, G. Di Caprio, G. Coppola, P. A. Netti, and P. Ferraro, “Recent advances in holographic 3D particle tracking,” Adv. Opt. Photonics 7(4), 713–755 (2015).
[Crossref]

Pham, H.

Pien, J.

F. R. N. C. Maia, A. MacDowell, S. Marchesini, H. A. Padmore, D. Y. Parkinson, J. Pien, A. Schirotzek, and C. Yang, “Compressive Phase Contrast Tomography,” Proc. SPIE 7800, 78000F (2010).
[Crossref]

Popescu, G.

Qian, B.

D. Xiao, Y. Chen, B. Qian, L. Yang, and Y. Kang, “Cone-beam computed tomography reconstruction accelerated with CUDA,” in Proceedings of IEEE conference on Biomedical Engineering and Informatics (IEEE, 2011), pp. 214–218.
[Crossref]

Rodrigues, C.

J. Stratton, N. Anssari, C. Rodrigues, I. J. Sung, N. Obeid, L. Chang, G. D. Liu, and W. M. Hwu, “Optimization and architecture effects on GPU computing workload performance,” in Proceedings of IEEE conference on Innovative Parallel Computing (IEEE, 2012), pp. 1–10.
[Crossref]

Roichman, Y.

Romanov, S. Y.

A. V. Goncharsky and S. Y. Romanov, “Supercomputer technologies in inverse problems of ultrasound tomography,” Inverse Probl. 29(7), 075004 (2013).
[Crossref]

Ruiter, N.

M. Birk, M. Zapf, M. Balzer, N. Ruiter, and J. Becker, “A comprehensive comparison of GPU-and FPGA-based acceleration of reflection image reconstruction for 3D ultrasound computer tomography,” J. Real-Time. Image. Proc. 9(1), 159–170 (2014).

Ruiter, N. V.

E. Kretzek, M. Zapf, M. Birk, H. Gemmeke, and N. V. Ruiter, “GPU based acceleration of 3D USCT image reconstruction with efficient integration into MATLAB,” Proc. SPIE 8675, 86750O (2013).
[Crossref]

Schafer, S.

P. B. Noël, A. M. Walczak, J. Xu, J. J. Corso, K. R. Hoffmann, and S. Schafer, “GPU-based cone beam computed tomography,” Comput. Methods Programs Biomed. 98(3), 271–277 (2010).
[Crossref] [PubMed]

Scherl, H.

H. Scherl, B. Keck, M. Kowarschik, and J. Hornegger, “Fast GPU-based CT reconstruction using the common unified device architecture (CUDA),” in Proceedings of IEEE conference on Nuclear Science (IEEE, 2007), pp. 4464–4466.
[Crossref]

Schirotzek, A.

F. R. N. C. Maia, A. MacDowell, S. Marchesini, H. A. Padmore, D. Y. Parkinson, J. Pien, A. Schirotzek, and C. Yang, “Compressive Phase Contrast Tomography,” Proc. SPIE 7800, 78000F (2010).
[Crossref]

Shaked, N. T.

Simon, B.

J. Bailleul, B. Simon, M. Debailleul, H. Liu, and O. Haeberlé, “GPU acceleration towards real-time image reconstruction in 3D tomographic diffractive microscopy,” Proc. SPIE 8437, 843707 (2012).
[Crossref]

Sobh, N.

Stratton, J.

J. Stratton, N. Anssari, C. Rodrigues, I. J. Sung, N. Obeid, L. Chang, G. D. Liu, and W. M. Hwu, “Optimization and architecture effects on GPU computing workload performance,” in Proceedings of IEEE conference on Innovative Parallel Computing (IEEE, 2012), pp. 1–10.
[Crossref]

Sung, I. J.

J. Stratton, N. Anssari, C. Rodrigues, I. J. Sung, N. Obeid, L. Chang, G. D. Liu, and W. M. Hwu, “Optimization and architecture effects on GPU computing workload performance,” in Proceedings of IEEE conference on Innovative Parallel Computing (IEEE, 2012), pp. 1–10.
[Crossref]

Sung, Y.

Walczak, A. M.

P. B. Noël, A. M. Walczak, J. Xu, J. J. Corso, K. R. Hoffmann, and S. Schafer, “GPU-based cone beam computed tomography,” Comput. Methods Programs Biomed. 98(3), 271–277 (2010).
[Crossref] [PubMed]

Waller, L.

N. Loomis, L. Waller, and G. Barbastathis, “High-speed phase recovery using chromatic transport of intensity computation in graphics processing units,” in Proc. Biomedical Optics and 3-D imaging (2010), paper JMA7.

Xiao, D.

D. Xiao, Y. Chen, B. Qian, L. Yang, and Y. Kang, “Cone-beam computed tomography reconstruction accelerated with CUDA,” in Proceedings of IEEE conference on Biomedical Engineering and Informatics (IEEE, 2011), pp. 214–218.
[Crossref]

Xu, J.

P. B. Noël, A. M. Walczak, J. Xu, J. J. Corso, K. R. Hoffmann, and S. Schafer, “GPU-based cone beam computed tomography,” Comput. Methods Programs Biomed. 98(3), 271–277 (2010).
[Crossref] [PubMed]

Yang, C.

F. R. N. C. Maia, A. MacDowell, S. Marchesini, H. A. Padmore, D. Y. Parkinson, J. Pien, A. Schirotzek, and C. Yang, “Compressive Phase Contrast Tomography,” Proc. SPIE 7800, 78000F (2010).
[Crossref]

Yang, L.

D. Xiao, Y. Chen, B. Qian, L. Yang, and Y. Kang, “Cone-beam computed tomography reconstruction accelerated with CUDA,” in Proceedings of IEEE conference on Biomedical Engineering and Informatics (IEEE, 2011), pp. 214–218.
[Crossref]

Ye, J. C.

Yoon, H.

K. Kim, H. Yoon, M. Diez-Silva, M. Dao, R. R. Dasari, and Y. Park, “High-resolution three-dimensional imaging of red blood cells parasitized by Plasmodium falciparum and in situ hemozoin crystals using optical diffraction tomography,” J. Biomed. Opt. 19(1), 011005 (2013).
[Crossref] [PubMed]

Yoon, J.

Zapf, M.

M. Birk, M. Zapf, M. Balzer, N. Ruiter, and J. Becker, “A comprehensive comparison of GPU-and FPGA-based acceleration of reflection image reconstruction for 3D ultrasound computer tomography,” J. Real-Time. Image. Proc. 9(1), 159–170 (2014).

E. Kretzek, M. Zapf, M. Birk, H. Gemmeke, and N. V. Ruiter, “GPU based acceleration of 3D USCT image reconstruction with efficient integration into MATLAB,” Proc. SPIE 8675, 86750O (2013).
[Crossref]

Adv. Opt. Photonics (1)

P. Memmolo, L. Miccio, M. Paturzo, G. Di Caprio, G. Coppola, P. A. Netti, and P. Ferraro, “Recent advances in holographic 3D particle tracking,” Adv. Opt. Photonics 7(4), 713–755 (2015).
[Crossref]

Biomed. Opt. Express (2)

Comput. Methods Programs Biomed. (1)

P. B. Noël, A. M. Walczak, J. Xu, J. J. Corso, K. R. Hoffmann, and S. Schafer, “GPU-based cone beam computed tomography,” Comput. Methods Programs Biomed. 98(3), 271–277 (2010).
[Crossref] [PubMed]

EURASIP J. Embed. Syst. (1)

N. Gac, S. Mancini, M. Desvignes, and D. Houzet, “High speed 3D tomography on CPU, GPU, and FPGA,” EURASIP J. Embed. Syst. 2008(1), 930250 (2008).
[Crossref]

IEEE Trans Comput Imaging (1)

M. G. McGaffin and J. A. Fessler, “Alternating dual updates algorithm for X-ray CT reconstruction on the GPU,” IEEE Trans Comput Imaging 1(3), 186–199 (2015).
[Crossref] [PubMed]

IEEE Trans. Acoust. Speech Signal Process. (1)

R. G. Keys, “Cubic convolution interpolation for digital image processing,” IEEE Trans. Acoust. Speech Signal Process. 29(6), 1153–1160 (1981).
[Crossref]

Inverse Probl. (1)

A. V. Goncharsky and S. Y. Romanov, “Supercomputer technologies in inverse problems of ultrasound tomography,” Inverse Probl. 29(7), 075004 (2013).
[Crossref]

J. Biomed. Opt. (1)

K. Kim, H. Yoon, M. Diez-Silva, M. Dao, R. R. Dasari, and Y. Park, “High-resolution three-dimensional imaging of red blood cells parasitized by Plasmodium falciparum and in situ hemozoin crystals using optical diffraction tomography,” J. Biomed. Opt. 19(1), 011005 (2013).
[Crossref] [PubMed]

J. Parallel Distrib. Comput. (1)

J. J. Fernández, J. M. Carazo, and I. García, “Three-dimensional reconstruction of cellular structures by electron microscope tomography and parallel computing,” J. Parallel Distrib. Comput. 64(2), 285–300 (2004).
[Crossref]

J. Real-Time. Image. Proc. (1)

M. Birk, M. Zapf, M. Balzer, N. Ruiter, and J. Becker, “A comprehensive comparison of GPU-and FPGA-based acceleration of reflection image reconstruction for 3D ultrasound computer tomography,” J. Real-Time. Image. Proc. 9(1), 159–170 (2014).

J. Struct. Biol. (1)

D. Castaño Díez, H. Mueller, and A. S. Frangakis, “Implementation and performance evaluation of reconstruction algorithms on graphics processors,” J. Struct. Biol. 157(1), 288–295 (2007).
[Crossref] [PubMed]

Nat. Methods (1)

W. Choi, C. Fang-Yen, K. Badizadegan, S. Oh, N. Lue, R. R. Dasari, and M. S. Feld, “Tomographic phase microscopy,” Nat. Methods 4(9), 717–719 (2007).
[Crossref] [PubMed]

Opt. Express (5)

Opt. Lett. (4)

Parallel Comput. (1)

Y. Okitsu, F. Ino, and K. Hagihara, “High-performance cone beam reconstruction using CUDA compatible GPUs,” Parallel Comput. 36(2), 129–141 (2010).
[Crossref]

Proc. SPIE (3)

F. R. N. C. Maia, A. MacDowell, S. Marchesini, H. A. Padmore, D. Y. Parkinson, J. Pien, A. Schirotzek, and C. Yang, “Compressive Phase Contrast Tomography,” Proc. SPIE 7800, 78000F (2010).
[Crossref]

J. Bailleul, B. Simon, M. Debailleul, H. Liu, and O. Haeberlé, “GPU acceleration towards real-time image reconstruction in 3D tomographic diffractive microscopy,” Proc. SPIE 8437, 843707 (2012).
[Crossref]

E. Kretzek, M. Zapf, M. Birk, H. Gemmeke, and N. V. Ruiter, “GPU based acceleration of 3D USCT image reconstruction with efficient integration into MATLAB,” Proc. SPIE 8675, 86750O (2013).
[Crossref]

Other (12)

N. Loomis, L. Waller, and G. Barbastathis, “High-speed phase recovery using chromatic transport of intensity computation in graphics processing units,” in Proc. Biomedical Optics and 3-D imaging (2010), paper JMA7.

G. Ortega, J. Lobera, M. Arroyo, I. García, and E. M. Garzon, “High performance computing for optical diffraction tomography,” in Proceedings of IEEE conference on High Performance Computing and Simulation (IEEE, 2012), pp. 195–201.
[Crossref]

D. Xiao, Y. Chen, B. Qian, L. Yang, and Y. Kang, “Cone-beam computed tomography reconstruction accelerated with CUDA,” in Proceedings of IEEE conference on Biomedical Engineering and Informatics (IEEE, 2011), pp. 214–218.
[Crossref]

H. Scherl, B. Keck, M. Kowarschik, and J. Hornegger, “Fast GPU-based CT reconstruction using the common unified device architecture (CUDA),” in Proceedings of IEEE conference on Nuclear Science (IEEE, 2007), pp. 4464–4466.
[Crossref]

A. C. Kak and M. Slaney, Principles of Computerized Tomographic Imaging, (SIAM, 2001).

D. C. Ghihlia and M. D. Pritt, Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software (Wiley, 1998).

N. T. Shaked, Z. Zalevsky, and L. L. Satterwhite, Biomedical Optical Phase Microscopy and Nanoscopy (Academic Press, 2012).

R. N. Bracewell, Two-Dimensional Imaging, (Prentice Hall, 1995).

J. D. Schmidt, Numerical Simulation of Optical Wave Propagation with Examples in MATLAB, (SPIE, 2010), Chap 2.

J. Stratton, N. Anssari, C. Rodrigues, I. J. Sung, N. Obeid, L. Chang, G. D. Liu, and W. M. Hwu, “Optimization and architecture effects on GPU computing workload performance,” in Proceedings of IEEE conference on Innovative Parallel Computing (IEEE, 2012), pp. 1–10.
[Crossref]

R. Qyvind, D. Geir, and M. Knut, “Fourier theory, wavelet analysis and nonlinear optimization,” http://www.uio.no/studier/emner/matnat/math/MAT-INF2360/v12/fft.pdf

G. Ruetsch and P. Micikevicius, “Optimizing matrix transpose in CUDA,” http://docs.nvidia.com/cuda/samples/6_Advanced/transpose/doc/MatrixTranspose.pdf

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Figures (8)

Fig. 1
Fig. 1

The Fourier slice theorem maps the Fourier transform of a 2-D projection into a radial plane in the 3-D Fourier space. (x0, y0, z0) and (kx0, kyo, kzo) are stationary coordinate systems in the image and Fourier spaces, respectively. (x, y, z) and (kx, ky, kz) are coordinate systems rotated around the y0 and ky0 axes, respectively, at angle θ . The cell rotation direction is indicated by the arrow around the y0 axis.

Fig. 2
Fig. 2

An efficient algorithm for quantitative phase extraction from off-axis holograms (Algorithm E in [28]).

Fig. 3
Fig. 3

A diagram of the UWLS algorithm for 2-D phase unwrapping, as described in [22]. The input wrapped phased map contains N/4 × N/4 pixels.

Fig. 4
Fig. 4

A diagram of the GPU implementation of the parallel algorithm for TPM reconstruction: (a) The offline initialization step performed once for every hologram set. (b) Online reconstruction using the GPU.

Fig. 5
Fig. 5

A comparison between the reconstruction results obtained for simulation data for various reconstruction implementations. (a) A schematic model of the input object. (b–e) axial slice, (f–i) coronal slice, (j–m) sagittal slice. Images (b), (f), and (j) are the true (input) RI distribution. Images (c), (g), and (k) are the results for the standard CPU reconstruction in Matlab. Images (d), (h), and (l) are the results for the efficient CPU implementation in C. Images (e), (i), and (m) are the results for the efficient GPU implementation with CUDA C. Colorbar represents RI values.

Fig. 6
Fig. 6

The dependency of the 3-D RI reconstruction quality in the resolution of the input holograms (a) A schematic model of the input object. (b–d) axial slice, (e–g) coronal slice, (h‑j) sagittal slice. Images (b), (e), and (h) are the reconstruction results for a 256 × 256 hologram set input, images (c), (f), and (i) are for the 512 × 512 hologram set input and images (d), (g), and (j) are for the 1024 × 1024 hologram set input. Colorbar represents RI values.

Fig. 7
Fig. 7

(a) Optical setup scheme for interferometric TPM with rotation of single cells. The system combines cell micro-manipulation for cell rotation and an external interferometric module for acquisition of off-axis holograms during cell rotation. MO: Microscope objective; S: sample; TL: Tube lens; M1˗M3: Mirrors; L1, L2: Lenses in 4f configuration; BS: Beam splitter; RR: Retro-reflector; P: Pinhole. (b-g) The reconstructed 3-D RI map of a T-cell suspended in a medium, as acquired with the experimental setup. The input for the reconstruction was 73 off-axis holograms taken in equal angular increments over a 180° range, each of which in the size of 256 × 256 pixels. Colorbar represents RI values, where 1.33 is the RI of the medium. (b-d) Reconstruction results using the efficient algorithm presented in Section 2 implemented in C language on the GPU. (b) Mid-sagittal slice; (c) Mid-coronal slice; (d) Mid-axial slice; (e-g) The coinciding cases for (b-d), but when implementing the conventional phase extraction and ODT in Matlab. These results show minimal loss of accuracy when implementing the proposed efficient algorithms.

Fig. 8
Fig. 8

Average reconstruction rates (fps) and speedups when comparing the CPU and GPU efficient implementations, for various input hologram sizes (a) Rates including reading and writing to/from the CPU and memory transfers to/from the GPU when relevant; (b) Rates not including reading and writing to/from the CPU.

Tables (1)

Tables Icon

Table 1 Calculation times in [ms] when comparing the CPU vs. GPU efficient implementations of the various stages of the reconstruction, for various hologram sizes.

Equations (3)

Equations on this page are rendered with MathJax. Learn more.

O P D ( θ ) = 0 h ( x , y ) ( n c e l l ( x , y , z ) n a m b i e n t ) d z ,
x n e w = 1 8 x 1 + 3 8 x 2 + 3 8 x 3 + 1 8 x 4 .
ψ ' ( x , y ) = φ ' ( x , y ) 2 π s i g n { φ ' ( x , y ) } f l o o r ( | φ ' ( x , y ) + s i g n ( φ ' ( x , y ) ) π | 2 π )

Metrics