Funded Work Related to Biomedical Imaging

• NSF DMS 1217161, 9/1/2012 – 8/30/2015. “Collaborative Research: Innovative, Integrated Strategies for Nonlinear Parametric Inversion.” Collaboration with Eric de Sturler, Serkan Gugercin, Christopher Beattie at Virginia Tech.
• NIH R01-CA154774 7/12/2011-6/30/2016. Co-PI. (PI: Sergio Fantini, Tufts BME), “Near-infrared spectral imaging of the breast for cancer detection and monitoring.”
• NSF 0139968 “Inverse Scattering Models and Algorithms for Functional Brain Imaging with Diffuse Optical Wavefields,” 9/01/02 – 8/31/05. co-PI. Eric Miller PI.
• NSF 0208548, “Toward a Unifed Approach to Diffuse Wave Inverse Problems,” 8/01/02 – 7/31/05. co-PI. Eric Miller PI.

Plenary Presentation

• Challenges in Modern Medical Image Reconstruction , Plenary Talk, SIAM Applied Linear Algebra, Valencia, Spain, 2012.

Magnetic Resonance Imaging

• W. S. Hoge, M. E. Kilmer, S. J. Haker, D. H. Brooks, W. E. Kyriakos, Fast Regularized Reconstruction of Non-Uniformly Subsampled Parallel MRI Data, International Symposium on Biomedical Imaging, 2006 Proceedings (peer-reviewed).
• W. S. Hoge, M. E. Kilmer, C. Zacarias-Almarcha, D. H. Brooks, Fast Regularized Reconstruction of Non-uniformly Subsampled Partial-Fourier Parallel MRI data , International Symposium on Biomedical Imaging, 2007 Proceedings (peer-reviewed).
• PATENT: Kilmer and Hoge, “Magnetic Resonance Imaging by Subspace Projection” Awarded 2010. http://www.patentgenius.com/patent/7869639.html
• Two-Parameter Selection Techniques for Projection-based Regularization Methods: Application to Partial-Fourier pMRI Follow up work to the two papers above. Slides presented at SIAM Annual Meeting in 2008. For the paper, please contact me.

Bio-Image Analysis

• Alexander Nectow, Misha E. Kilmer and David Kaplan, Quantitative Assessment of Nerve Cell Alignment. Tissue Engineering Part C: Methods, to appear 2013.
• Alexander Nectow, Eun Seok, David Kaplan and Misha E. Kilmer, A Statistical Algorithm for Assessing Cellular Alignment. Journal of Biomedical Materials Research: Part A, 101 (3), pages 884-91, 2012.

X-Ray CT

• Oguz Semerci, Ning Hao, Misha E. Kilmer, Eric L. Miller, Tensor Based Formulation and Nuclear Norm Regularization for Multienergy Computed Tomography, submitted to IEEE Transactions on Image Processing, Oct. 2012. In second round review, Apr. 2013.
• Slides which show some X-ray CT results: A t-SVD-based Nuclear Norm with Imaging Applications , ILAS Meeting, Providence RI, June 2013.
• James Nagy and Misha E. Kilmer, Kronecker Product Approximation for Three-Dimensional Imaging Applications, IEEE Trans. Image Proc., Vol. 15, No. 3, Mar. 2006.
(see also slides below)

Structured Matrices and Tensors Arising in Medical Imaging Applications

• Slides A t-SVD-based Nuclear Norm with Imaging Applications , ILAS Meeting, Providence RI, June 2013.
• Misha E. Kilmer and James Nagy, Kronecker Product Approximations for Dense Block-Toeplitz-plus-Hankle Matrices, Numerical Linear Algebra with Applications, Vol. 14, Issue 8, Oct. 2007, pp. 581-602.
• Damon Hyde, Misha E. Kilmer, Eric Miller, Dana Brooks Analysis and Exploitation of Matrix Structure Arising in Linearized Inverse Scattering, SIAM Journal on Matrix Anal. Appl., Vol. 29, pp. 1065-1082, 2007.
• James Nagy and Misha E. Kilmer, Kronecker Product Approximation for Three-Dimensional Imaging Applications, IEEE Trans. Image Proc., Vol. 15, No. 3, Mar. 2006.
• Kronecker Product Approximation for Preconditioning in 3D Imaging Applications , Follow up to 2006 article, Slides presented at SIAM Annual Meeting in 2006.
• Slides, similar talk, presented at SIAM Applied Linear Algebra Meeting, 2006.

Parametric Level Sets for Tomographic Reconstruction

• Alireza Aghasi, Eric L. Miller, and Misha E. Kilmer, Parametric Level Set Methods for Inverse Problems, SIAM J. Imaging Sci. 4, 2011, pp. 618-650.
• Fridrik Larusson, Pamela G. Anderson, Elizabeth Rosenberg, Misha E. Kilmer, Angelo Sassaroli, Sergio Fantini, Eric L. Miller, Parametric Estimation of 3D tubular Structures for Diffuse Optical Tomography, Biomedical Optics Express, vol 4, pages 271-286, 2013.

Fast Algorithms for Tomographic Problems involving Non-linear Forward Model

• Misha E. Kilmer and Eric de Sturler, Recycling Subspace Information for Di?use Optical Tomography, SIAM J. Sci. Comput., Vol. 27, No. 6, pp. 2140-2166, 2006.
• Slides from talk at the Tufts-Schlumberger Computational and Applied Math Seminar on the above paper.
• Eric de Sturler and Misha E. Kilmer, A Regularized Gauss-Newton Trust Region Approach to Imaging in Diffuse Optical Tomography, Copper Mountain 2010 Special Issues, SIAM J. Sci. Comput. 33, 2011, pp. 3057-3086.
• Corresponding Slides from SIAM CS&E, 2009

Earlier Work, Modeling and Regularized Inversion

• Misha E. Kilmer, Eric L. Miller, David A. Boas, Dana H. Brooks, Charles A. DiMarzio, and Richard J. Gaudette, Direct Object Localization and Characterization from Di?use Photon Density Wave Data, Jan. 1999 Proceedings of the SPIE Photonics West Conference, 1999.
• Rick Gaudette, Dana Brooks, Charles DiMarzio, Misha Kilmer, Eric Miller, Tom Gaudette, David Boas, A Comparison Study of Linear Reconstruction Techniques for Di?use Optical Tomographic Imaging of the Absorption Coe?cient. Physics in Medicine and Biology, Vol. 45, No. 4, pp. 1051-1070, 2000.
• D. Boas, D. Brooks, E. Miller, C. DiMarzio, M. Kilmer, R. Gaudette, Q. Zhang, Imaging the Body with Di?use Optical Tomography, IEEE Signal Processing Magazine, Vol. 18, No. 6, pp. 57-75, 2001.
• Ang Li, E. Miller, M. Kilmer, T. Brukilacchio, T. Chaves, J. Stott, Q. Zhang, T. Wu, M. Chorlton, R. Moore, D. Kopans, D. Boas, Tomographic Optical Breast Imaging Guided by 3-D Mammography, Applied Optics, 2003.
• Eric Miller, Margaret Cheney, Misha E. Kilmer, Gregory Boverman, Ang Li, David Boas, Feature-Enhancing Inverse Methods for Limited-View Tomographic Imaging Problems , Subsurface Sensing Technologies and Applications, Vol. 4, No. 4, October 2003, pp. 327-353, 2003.
• Misha Kilmer, Eric Miller, Marco Enriquez, David Boas, Cortical Constraint Method for Di?use Optical Brain Imaging , SPIE Proceedings of the Annual Meeting, Vol. 5559, Aug. 2004, pp. 381-391.
• Ang Li, Greg Boverman, Yiheng Zhang, Dana Brooks, Quan Zhang, Elizabeth Hillman, Misha Kilmer, Eric Miller, David Boas, An Optimal Linear Inverse Solution Given Multiple Priors in Diffuse Optical Tomography Applied Optics, Vol 44, 2005.

• Misha E. Kilmer, Eric L. Miller, David Boas, Dana Brooks, A Shape-Based Reconstruction Technique for DPDW Data , Optics Express (focused issue), Vol. 7, No. 13, pp. 461, 2000.
• Misha E. Kilmer, Eric Miller, Alethea Barbaro, David Boas, 3D Shape-Based Imaging for Di?use Optical Tomography, Applied Optics, Vol. 42, pp. 3129-3144, 2003.
• Misha Kilmer, Eric Miller, Marco Enriquez, David Boas, Cortical Constraint Method for Di?use Optical Brain Imaging , SPIE Proceedings of the Annual Meeting, Vol. 5559, Aug. 2004, pp. 381-391.
• Slides on Cortical Constraint Method , presentation at the SPIE Meeting.

Maintained by: Misha Kilmer NO SLIDES MAY BE USED, ALTERED OR REPRODUCED WITHOUT WRITTEN CONSENT OF Misha Kilmer.