B. Banerjee, D. Roy, and R. M. Vasu, “A pseudo-dynamic sub-optimal filter for elastography under static loading and measurements,” Phys. Med. Biol. 54, 285–305 (2009).

[CrossRef]

B. Banerjee, D. Roy, and R. M. Vasu, “A pseudo-dynamical systems approach to a class of inverse problems in engineering,” Proc. R. Soc. A 465, 1561–1579 (2009).

[CrossRef]

A. D. Zacharopoulos, M. Schweiger, V. Kolehmainen, and S. Arridge, “3D shape based reconstruction of experimental data in diffuse optical tomography,” Opt. Express 17, 18940–18956(2009).

[CrossRef]

S. Gupta, P. K. Yalavarthy, D. Roy, D. Piao, and R. M. Vasu, “Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography,” Med. Phys. 36, 5559–5567 (2009).

[CrossRef]

B. Banerjee, D. Roy, and R. M. Vasu, “Efficient implementations of a pseudo-dynamical stochastic filtering strategy for static elastography,” Med. Phys. 36, 3470–3476 (2009).

[CrossRef]
[PubMed]

P. K. Yalavarthy, B. W. Pogue, H. Dehghani, and K. D. Paulsen, “Weight-matrix structured regularization provides optimal generalized least-squares estimate in diffuse optical tomography,” Med. Phys. 34, 2085–2098 (2007).

[CrossRef]
[PubMed]

M. Schweiger, S. R. Arridge, and I. Nissila, “Gauss–Newton method for image reconstruction in diffuse optical tomography,” Phys. Med. Biol. 50, 2365–2386 (2005).

[CrossRef]
[PubMed]

J. H. Kotecha and P. M. Djuric, “Gaussian sum particle filtering,” IEEE Trans. Signal Process. 51, 2602–2612 (2003).

[CrossRef]

V. Kolehmainen, S. Prince, S. R. Arridge, and J. P. Kaipo, “State-estimation approach to the nonstationary optical tomography problem,” J. Opt. Soc. Am. A 20, 876–889 (2003).

[CrossRef]

S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “Interpreting hemoglobin and water concentration, oxygen saturation and scattering measured in vivo by near-infrared breast tomography,” Proc. Natl. Acad. Sci. USA 100, 12349–12354 (2003).

[CrossRef]
[PubMed]

S. Arulampalam, N. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process. 50, 174–188(2002).

[CrossRef]

M. J. Eppstein, D. J. Hawrysz, A. Godavarty, and E. M. Sevick-Muraca, “Three-dimensional, Baysian image reconstruction from sparse and noisy data sets: near-infrared fluorescence tomography,” Proc. Natl. Acad. Sci. USA 99, 9619–9624 (2002).

[CrossRef]
[PubMed]

M. J. Eppstein, D. E. Dougherty, D. J. Hawrysz, and E. M. Sevick-Muraca, “Three-dimensional Bayesian optical image reconstruction with domain decomposition,” IEEE Trans. Med. Imag. 20, 147–163 (2001).

[CrossRef]

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75(2001).

[CrossRef]

B. W. Pogue, S. P. Poplack, T. O. McBride, W. A. Wells, O. K. S., U. L. Osterberg, and K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218, 261–266 (2001).

[PubMed]

D. Roy, “A new numeric-analytical principle for nonlinear deterministic and stochastic dynamical systems,” Proc. R. Soc. London Ser. A 457, 539–566 (2001).

[CrossRef]

D. Roy, “Explorations of the phase space linearization method for deterministic and stochastic non-linear dynamical systems,” Nonlinear Dyn. 23, 225–258 (2000).

[CrossRef]

B. J. Tromberg, N. Shah, R. Lanning, A. Cerussi, J. Espinoza, T. Pham, L. Svaasand, and J. Butler, “Non-invasive in vivocharacterization of breast tumors using photon migration spectroscopy,” Neoplasia 2, 26–40 (2000).

[CrossRef]
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[CrossRef]

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[CrossRef]

D. W. Marquardt, “An algorithm for least squares estimation of nonlinear parameters,” J. Soc. Ind. Appl. Math. 11, 431–441(1963).

[CrossRef]

K. Levenberg, “A method for the solution of certain nonlinear problems in least squares,” Quart. Appl. Math. 2, 164–168(1944).

A. Doucet, S. Godsill, and C. Andrieu, “On sequential Monte Carlo sampling methods for Bayesian filtering,” Stat. Comput. 10, 197–208 (2000).

[CrossRef]

M. Schweiger, S. R. Arridge, and I. Nissila, “Gauss–Newton method for image reconstruction in diffuse optical tomography,” Phys. Med. Biol. 50, 2365–2386 (2005).

[CrossRef]
[PubMed]

V. Kolehmainen, S. Prince, S. R. Arridge, and J. P. Kaipo, “State-estimation approach to the nonstationary optical tomography problem,” J. Opt. Soc. Am. A 20, 876–889 (2003).

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[CrossRef]

S. Arulampalam, N. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process. 50, 174–188(2002).

[CrossRef]

B. Banerjee, D. Roy, and R. M. Vasu, “Efficient implementations of a pseudo-dynamical stochastic filtering strategy for static elastography,” Med. Phys. 36, 3470–3476 (2009).

[CrossRef]
[PubMed]

B. Banerjee, D. Roy, and R. M. Vasu, “A pseudo-dynamic sub-optimal filter for elastography under static loading and measurements,” Phys. Med. Biol. 54, 285–305 (2009).

[CrossRef]

B. Banerjee, D. Roy, and R. M. Vasu, “A pseudo-dynamical systems approach to a class of inverse problems in engineering,” Proc. R. Soc. A 465, 1561–1579 (2009).

[CrossRef]

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75(2001).

[CrossRef]

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75(2001).

[CrossRef]

B. J. Tromberg, N. Shah, R. Lanning, A. Cerussi, J. Espinoza, T. Pham, L. Svaasand, and J. Butler, “Non-invasive in vivocharacterization of breast tumors using photon migration spectroscopy,” Neoplasia 2, 26–40 (2000).

[CrossRef]
[PubMed]

B. J. Tromberg, N. Shah, R. Lanning, A. Cerussi, J. Espinoza, T. Pham, L. Svaasand, and J. Butler, “Non-invasive in vivocharacterization of breast tumors using photon migration spectroscopy,” Neoplasia 2, 26–40 (2000).

[CrossRef]
[PubMed]

S. Arulampalam, N. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process. 50, 174–188(2002).

[CrossRef]

A. Doucet, N. de Freitas, and N. Gordon, Sequential Monte Carlo Methods in Practice (Academic, 2001).

P. K. Yalavarthy, B. W. Pogue, H. Dehghani, and K. D. Paulsen, “Weight-matrix structured regularization provides optimal generalized least-squares estimate in diffuse optical tomography,” Med. Phys. 34, 2085–2098 (2007).

[CrossRef]
[PubMed]

S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “Interpreting hemoglobin and water concentration, oxygen saturation and scattering measured in vivo by near-infrared breast tomography,” Proc. Natl. Acad. Sci. USA 100, 12349–12354 (2003).

[CrossRef]
[PubMed]

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75(2001).

[CrossRef]

J. H. Kotecha and P. M. Djuric, “Gaussian sum particle filtering,” IEEE Trans. Signal Process. 51, 2602–2612 (2003).

[CrossRef]

J. H. Kotecha and P. M. Djuric, “Gaussian sum particle filtering for dynamic state space models,” in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2001), pp. 3465–3468.

A. Doucet, S. Godsill, and C. Andrieu, “On sequential Monte Carlo sampling methods for Bayesian filtering,” Stat. Comput. 10, 197–208 (2000).

[CrossRef]

A. Doucet, N. de Freitas, and N. Gordon, Sequential Monte Carlo Methods in Practice (Academic, 2001).

M. J. Eppstein, D. E. Dougherty, D. J. Hawrysz, and E. M. Sevick-Muraca, “Three-dimensional Bayesian optical image reconstruction with domain decomposition,” IEEE Trans. Med. Imag. 20, 147–163 (2001).

[CrossRef]

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[CrossRef]

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[CrossRef]

M. J. Eppstein, D. J. Hawrysz, A. Godavarty, and E. M. Sevick-Muraca, “Three-dimensional, Baysian image reconstruction from sparse and noisy data sets: near-infrared fluorescence tomography,” Proc. Natl. Acad. Sci. USA 99, 9619–9624 (2002).

[CrossRef]
[PubMed]

M. J. Eppstein, D. E. Dougherty, D. J. Hawrysz, and E. M. Sevick-Muraca, “Three-dimensional Bayesian optical image reconstruction with domain decomposition,” IEEE Trans. Med. Imag. 20, 147–163 (2001).

[CrossRef]

M. J. Eppstein, D. E. Dougherty, T. L. Troy, and E. M. Sevic-Muraca, “Biomedical optical tomography using dynamic parametrization and Bayesian conditioning on photon migration measurements,” Appl. Opt. 38, 2138–2150 (1999).

[CrossRef]

B. J. Tromberg, N. Shah, R. Lanning, A. Cerussi, J. Espinoza, T. Pham, L. Svaasand, and J. Butler, “Non-invasive in vivocharacterization of breast tumors using photon migration spectroscopy,” Neoplasia 2, 26–40 (2000).

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D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75(2001).

[CrossRef]

S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “Interpreting hemoglobin and water concentration, oxygen saturation and scattering measured in vivo by near-infrared breast tomography,” Proc. Natl. Acad. Sci. USA 100, 12349–12354 (2003).

[CrossRef]
[PubMed]

M. J. Eppstein, D. J. Hawrysz, A. Godavarty, and E. M. Sevick-Muraca, “Three-dimensional, Baysian image reconstruction from sparse and noisy data sets: near-infrared fluorescence tomography,” Proc. Natl. Acad. Sci. USA 99, 9619–9624 (2002).

[CrossRef]
[PubMed]

A. Doucet, S. Godsill, and C. Andrieu, “On sequential Monte Carlo sampling methods for Bayesian filtering,” Stat. Comput. 10, 197–208 (2000).

[CrossRef]

S. Arulampalam, N. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process. 50, 174–188(2002).

[CrossRef]

A. Doucet, N. de Freitas, and N. Gordon, Sequential Monte Carlo Methods in Practice (Academic, 2001).

N. J. Gordon, D. J. Salmond, and A. F. M. Smith, “Novel approach to nonlinear/non-Gaussian Bayesian state estimation,” in IEE Proceedings F Radar and Signal Processing (IEEE, 1993), Vol. 140, pp. 107–113.

[CrossRef]

S. Gupta, P. K. Yalavarthy, D. Roy, D. Piao, and R. M. Vasu, “Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography,” Med. Phys. 36, 5559–5567 (2009).

[CrossRef]

H. W. Engl, M. Hanke, and A. Neubauer, Regularization of the Inverse Problem (Academic, 1996).

[CrossRef]

P. C. Hansen, “Analysis of discrete ill-posed problems by means of the L-curve,” SIAM Rev. 34, 561–580 (1992).

[CrossRef]

M. J. Eppstein, D. J. Hawrysz, A. Godavarty, and E. M. Sevick-Muraca, “Three-dimensional, Baysian image reconstruction from sparse and noisy data sets: near-infrared fluorescence tomography,” Proc. Natl. Acad. Sci. USA 99, 9619–9624 (2002).

[CrossRef]
[PubMed]

M. J. Eppstein, D. E. Dougherty, D. J. Hawrysz, and E. M. Sevick-Muraca, “Three-dimensional Bayesian optical image reconstruction with domain decomposition,” IEEE Trans. Med. Imag. 20, 147–163 (2001).

[CrossRef]

S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “Interpreting hemoglobin and water concentration, oxygen saturation and scattering measured in vivo by near-infrared breast tomography,” Proc. Natl. Acad. Sci. USA 100, 12349–12354 (2003).

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D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75(2001).

[CrossRef]

S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “Interpreting hemoglobin and water concentration, oxygen saturation and scattering measured in vivo by near-infrared breast tomography,” Proc. Natl. Acad. Sci. USA 100, 12349–12354 (2003).

[CrossRef]
[PubMed]

A. D. Zacharopoulos, M. Schweiger, V. Kolehmainen, and S. Arridge, “3D shape based reconstruction of experimental data in diffuse optical tomography,” Opt. Express 17, 18940–18956(2009).

[CrossRef]

V. Kolehmainen, S. Prince, S. R. Arridge, and J. P. Kaipo, “State-estimation approach to the nonstationary optical tomography problem,” J. Opt. Soc. Am. A 20, 876–889 (2003).

[CrossRef]

J. H. Kotecha and P. M. Djuric, “Gaussian sum particle filtering,” IEEE Trans. Signal Process. 51, 2602–2612 (2003).

[CrossRef]

J. H. Kotecha and P. M. Djuric, “Gaussian sum particle filtering for dynamic state space models,” in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2001), pp. 3465–3468.

B. J. Tromberg, N. Shah, R. Lanning, A. Cerussi, J. Espinoza, T. Pham, L. Svaasand, and J. Butler, “Non-invasive in vivocharacterization of breast tumors using photon migration spectroscopy,” Neoplasia 2, 26–40 (2000).

[CrossRef]
[PubMed]

K. Levenberg, “A method for the solution of certain nonlinear problems in least squares,” Quart. Appl. Math. 2, 164–168(1944).

R. Lipster and A. Shiryaev, Statistics of Random Processes(Academic, 2001).

D. W. Marquardt, “An algorithm for least squares estimation of nonlinear parameters,” J. Soc. Ind. Appl. Math. 11, 431–441(1963).

[CrossRef]

S. Arulampalam, N. Maskell, N. Gordon, and T. Clapp, “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,” IEEE Trans. Signal Process. 50, 174–188(2002).

[CrossRef]

B. W. Pogue, S. P. Poplack, T. O. McBride, W. A. Wells, O. K. S., U. L. Osterberg, and K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218, 261–266 (2001).

[PubMed]

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, and Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75(2001).

[CrossRef]

K. Murphy and S. Russell, “Rao-Blackwellised particle filtering for dynamic Bayesian networks,” in Sequential Monte Carlo Methods in Practice, A.Doucet, N.de Freitas, and N.Gordon, eds. (Academic2001), pp. 499–515.

H. W. Engl, M. Hanke, and A. Neubauer, Regularization of the Inverse Problem (Academic, 1996).

[CrossRef]

M. Schweiger, S. R. Arridge, and I. Nissila, “Gauss–Newton method for image reconstruction in diffuse optical tomography,” Phys. Med. Biol. 50, 2365–2386 (2005).

[CrossRef]
[PubMed]

B. W. Pogue, S. P. Poplack, T. O. McBride, W. A. Wells, O. K. S., U. L. Osterberg, and K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218, 261–266 (2001).

[PubMed]

P. K. Yalavarthy, B. W. Pogue, H. Dehghani, and K. D. Paulsen, “Weight-matrix structured regularization provides optimal generalized least-squares estimate in diffuse optical tomography,” Med. Phys. 34, 2085–2098 (2007).

[CrossRef]
[PubMed]

S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “Interpreting hemoglobin and water concentration, oxygen saturation and scattering measured in vivo by near-infrared breast tomography,” Proc. Natl. Acad. Sci. USA 100, 12349–12354 (2003).

[CrossRef]
[PubMed]

B. W. Pogue, S. P. Poplack, T. O. McBride, W. A. Wells, O. K. S., U. L. Osterberg, and K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218, 261–266 (2001).

[PubMed]

B. J. Tromberg, N. Shah, R. Lanning, A. Cerussi, J. Espinoza, T. Pham, L. Svaasand, and J. Butler, “Non-invasive in vivocharacterization of breast tumors using photon migration spectroscopy,” Neoplasia 2, 26–40 (2000).

[CrossRef]
[PubMed]

S. Gupta, P. K. Yalavarthy, D. Roy, D. Piao, and R. M. Vasu, “Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography,” Med. Phys. 36, 5559–5567 (2009).

[CrossRef]

P. K. Yalavarthy, B. W. Pogue, H. Dehghani, and K. D. Paulsen, “Weight-matrix structured regularization provides optimal generalized least-squares estimate in diffuse optical tomography,” Med. Phys. 34, 2085–2098 (2007).

[CrossRef]
[PubMed]

S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “Interpreting hemoglobin and water concentration, oxygen saturation and scattering measured in vivo by near-infrared breast tomography,” Proc. Natl. Acad. Sci. USA 100, 12349–12354 (2003).

[CrossRef]
[PubMed]

B. W. Pogue, S. P. Poplack, T. O. McBride, W. A. Wells, O. K. S., U. L. Osterberg, and K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218, 261–266 (2001).

[PubMed]

S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “Interpreting hemoglobin and water concentration, oxygen saturation and scattering measured in vivo by near-infrared breast tomography,” Proc. Natl. Acad. Sci. USA 100, 12349–12354 (2003).

[CrossRef]
[PubMed]

B. W. Pogue, S. P. Poplack, T. O. McBride, W. A. Wells, O. K. S., U. L. Osterberg, and K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218, 261–266 (2001).

[PubMed]

B. Banerjee, D. Roy, and R. M. Vasu, “A pseudo-dynamic sub-optimal filter for elastography under static loading and measurements,” Phys. Med. Biol. 54, 285–305 (2009).

[CrossRef]

B. Banerjee, D. Roy, and R. M. Vasu, “Efficient implementations of a pseudo-dynamical stochastic filtering strategy for static elastography,” Med. Phys. 36, 3470–3476 (2009).

[CrossRef]
[PubMed]

S. Gupta, P. K. Yalavarthy, D. Roy, D. Piao, and R. M. Vasu, “Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography,” Med. Phys. 36, 5559–5567 (2009).

[CrossRef]

B. Banerjee, D. Roy, and R. M. Vasu, “A pseudo-dynamical systems approach to a class of inverse problems in engineering,” Proc. R. Soc. A 465, 1561–1579 (2009).

[CrossRef]

D. Roy, “A new numeric-analytical principle for nonlinear deterministic and stochastic dynamical systems,” Proc. R. Soc. London Ser. A 457, 539–566 (2001).

[CrossRef]

D. Roy, “Explorations of the phase space linearization method for deterministic and stochastic non-linear dynamical systems,” Nonlinear Dyn. 23, 225–258 (2000).

[CrossRef]

K. Murphy and S. Russell, “Rao-Blackwellised particle filtering for dynamic Bayesian networks,” in Sequential Monte Carlo Methods in Practice, A.Doucet, N.de Freitas, and N.Gordon, eds. (Academic2001), pp. 499–515.

B. W. Pogue, S. P. Poplack, T. O. McBride, W. A. Wells, O. K. S., U. L. Osterberg, and K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218, 261–266 (2001).

[PubMed]

N. J. Gordon, D. J. Salmond, and A. F. M. Smith, “Novel approach to nonlinear/non-Gaussian Bayesian state estimation,” in IEE Proceedings F Radar and Signal Processing (IEEE, 1993), Vol. 140, pp. 107–113.

[CrossRef]

A. D. Zacharopoulos, M. Schweiger, V. Kolehmainen, and S. Arridge, “3D shape based reconstruction of experimental data in diffuse optical tomography,” Opt. Express 17, 18940–18956(2009).

[CrossRef]

M. Schweiger, S. R. Arridge, and I. Nissila, “Gauss–Newton method for image reconstruction in diffuse optical tomography,” Phys. Med. Biol. 50, 2365–2386 (2005).

[CrossRef]
[PubMed]

M. J. Eppstein, D. J. Hawrysz, A. Godavarty, and E. M. Sevick-Muraca, “Three-dimensional, Baysian image reconstruction from sparse and noisy data sets: near-infrared fluorescence tomography,” Proc. Natl. Acad. Sci. USA 99, 9619–9624 (2002).

[CrossRef]
[PubMed]

M. J. Eppstein, D. E. Dougherty, D. J. Hawrysz, and E. M. Sevick-Muraca, “Three-dimensional Bayesian optical image reconstruction with domain decomposition,” IEEE Trans. Med. Imag. 20, 147–163 (2001).

[CrossRef]

B. J. Tromberg, N. Shah, R. Lanning, A. Cerussi, J. Espinoza, T. Pham, L. Svaasand, and J. Butler, “Non-invasive in vivocharacterization of breast tumors using photon migration spectroscopy,” Neoplasia 2, 26–40 (2000).

[CrossRef]
[PubMed]

R. Lipster and A. Shiryaev, Statistics of Random Processes(Academic, 2001).

N. J. Gordon, D. J. Salmond, and A. F. M. Smith, “Novel approach to nonlinear/non-Gaussian Bayesian state estimation,” in IEE Proceedings F Radar and Signal Processing (IEEE, 1993), Vol. 140, pp. 107–113.

[CrossRef]

S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “Interpreting hemoglobin and water concentration, oxygen saturation and scattering measured in vivo by near-infrared breast tomography,” Proc. Natl. Acad. Sci. USA 100, 12349–12354 (2003).

[CrossRef]
[PubMed]

S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “Interpreting hemoglobin and water concentration, oxygen saturation and scattering measured in vivo by near-infrared breast tomography,” Proc. Natl. Acad. Sci. USA 100, 12349–12354 (2003).

[CrossRef]
[PubMed]

B. J. Tromberg, N. Shah, R. Lanning, A. Cerussi, J. Espinoza, T. Pham, L. Svaasand, and J. Butler, “Non-invasive in vivocharacterization of breast tumors using photon migration spectroscopy,” Neoplasia 2, 26–40 (2000).

[CrossRef]
[PubMed]

S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “Interpreting hemoglobin and water concentration, oxygen saturation and scattering measured in vivo by near-infrared breast tomography,” Proc. Natl. Acad. Sci. USA 100, 12349–12354 (2003).

[CrossRef]
[PubMed]

B. J. Tromberg, N. Shah, R. Lanning, A. Cerussi, J. Espinoza, T. Pham, L. Svaasand, and J. Butler, “Non-invasive in vivocharacterization of breast tumors using photon migration spectroscopy,” Neoplasia 2, 26–40 (2000).

[CrossRef]
[PubMed]

B. Banerjee, D. Roy, and R. M. Vasu, “A pseudo-dynamical systems approach to a class of inverse problems in engineering,” Proc. R. Soc. A 465, 1561–1579 (2009).

[CrossRef]

S. Gupta, P. K. Yalavarthy, D. Roy, D. Piao, and R. M. Vasu, “Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography,” Med. Phys. 36, 5559–5567 (2009).

[CrossRef]

B. Banerjee, D. Roy, and R. M. Vasu, “Efficient implementations of a pseudo-dynamical stochastic filtering strategy for static elastography,” Med. Phys. 36, 3470–3476 (2009).

[CrossRef]
[PubMed]

B. Banerjee, D. Roy, and R. M. Vasu, “A pseudo-dynamic sub-optimal filter for elastography under static loading and measurements,” Phys. Med. Biol. 54, 285–305 (2009).

[CrossRef]

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