Frontiers in Computer
Vision - a CVPR 2012 workshop (FiCV
2012), Providence, RI, 2012. ICCV Workshop on
Information Theory in Computer Vision and Pattern Recognition (IWITCVPR
2011), Barcelona, Spain, 2011. Energy Minimization
Methods in Computer Vision and Pattern Recognition (EMMCVPR 2005), St.
Augustine, FL, November 2005. Energy Minimization Methods
in Computer Vision and Pattern Recognition (EMMCVPR 2003), Lisbon,
Portugal, July 2003. Mathematical Methods in
Biomedical Image Analysis (MMBIA
2001), Kauai, HI, December 2001. Neural Information
Processing Systems (NIPS) Workshop on "Statistical and
Structural models for Network Vision", Vail, CO, December 1995. Neural Information
Processing Systems (NIPS) Workshop on "Deterministic Annealing
and Combinatorial Optimization", Vail, CO, December 1992.
Neil Smith's RaceSpace face database containing
normalized face images from different races (partially supported
by NSF IIS 1065081). HOSVD denoising for
grayscale and color images. We acknowledge support from the
National Science Foundation (NSF IIS 1143963). Matlab code for grayscale and color image compression.
Matlab Toolbox for 1-D and
2-D Wavelet Density Estimation available at Adrian
Peter's site. CalFish_100: Fish Shape
Database. We acknowledge the Department
of Ichthyology, California Academy of Sciences for
providing us with the source images from which the shape
database was created and the support of the National Science
Foundation (NSF IIS 0307712). Non-rigid matching research
summary along with code available here. We acknowledge
support from the National Science Foundation (NSF IIS 0196457). Xiaohui Huang, Chengliang Yang, Sanjay
Ranka, Anand Rangarajan, Supervoxel-based
segmentation of 3D imagery with optical flow integration for spatiotemporal
processing, IPSJ Transactions on Computer Vision and Applications,
(accepted May 2018).
Birmingham Hang Guan, Anand
Rangarajan, Image stacks as parametric surfaces:
Application to image registration, IEEE Transactions on Image
Processing (accepted July 2018).
Yuan Zhou, Anand Rangarajan, Paul D. Gader, A Gaussian mixture model representation of endmember variability in hyperspectral unmixing, IEEE Transactions on Image Processing, 27(5): 2242-2256 (2018).
Subit Chakrabarti, Jasmeet Judge, Tara Bongiovanni, Anand Rangarajan, Sanjay Ranka, Spatial scaling using temporal correlations and ensemble learning to obtain high-resolution soil moisture, IEEE Transactions on Geoscience and Remote Sensing, 56(3): 1238-1250 (2018).
Yupeng Yan, Anand Rangarajan, Sanjay Ranka, An Efficient Deep Representation based Framework for Large-Scale Terrain Classification, International Conference on Pattern Recognition, (accepted April 2018).
Yuan Zhou, Anand Rangarajan, Paul D. Gader, Nonrigid registration of hyperspectral and color images with vastly different spatial and spectral resolutions for spectral unmixing and pansharpening, IEEE CVPR Workshops, pp. 1571-1579 (2017).
Rana Haber, Anand Rangarajan, Nenad Mijatovic, Anthony O. Smith, Adrian M. Peter, Functional Data Classification by Discriminative Interpolation with Features. In International Work Conference on Time Series Analysis, pp. 1120-1131, 2017.
Yupeng Yan, Manu Sethi, Anand Rangarajan, Sanjay Ranka, Super-Scalable Computation Framework for Automated Terrain Identification. DASC/PiCom/DataCom/CyberSciTech 2017: 1127-1134
Nenad Mijatovic, Rana Haber, Anand Rangarajan, Anthony O. Smith, Adrian M. Peter, Time Series Data Classification using Discriminative Interpolation with Sparsity, International Conference on Computational Science and Computational Intelligence, pp. 1-6, 2017.
John Corring, Anand Rangarajan, Resonant Deformable Matching: Simultaneous Registration and Reconstruction. ECCV (6) 2016: 51-68
Chengliang Yang, Manu Sethi, Anand Rangarajan, Sanjay Ranka: Supervoxel-Based Segmentation of 3D Volumetric Images. ACCV (1) 2016: 37-53
Yuan Zhou, Anand Rangarajan, Paul D. Gader, A spatial compositional model for linear unmixing and endmember uncertainty estimation. IEEE Transactions on Image Processing, 25(12): 5987-6002 (2016).
Subit Chakrabarti, Jasmeet Judge, Anand Rangarajan, Sanjay Ranka, Utilizing self-regularized regressive models to downscale microwave brightness temperatures for agricultural land covers in the SMAPVEX-12 region, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(2): 478-488 (2017).
Birmingham H. Guan, John Corring, Manu Sethi, Sanjay Ranka, Anand Rangarajan, Image stack surface area minimization for groupwise and multimodal affine registration. ICPR 2016: 4196-4201
Mark Moyou, John Corring, Adrian M. Peter and Anand Rangarajan, A Grassmannian Graph approach to affine invariant feature matching, arXiv preprint, arXiv:1601.07648v2 [cs.CV], 2016.
Yan Deng, Anand Rangarajan and Baba
Vemuri, Supervised learning for brain MR
segmentation via fusion of partially labeled multiple atlases, IEEE
International Symposium on Biomedical Imaging (ISBI), 2016.
Yupeng Yan, Manu Sethi, Anand
Rangarajan, Ranga Raju Vatsavai and Sanjay Ranka, Graph-Based Semi-Supervised
Classification on Very High Resolution Remote Sensing Images,
International Journal of Big Data Intelligence (IJBDI), (in press), 2016. Kushal Arora and Anand Rangarajan, A compositional approach to language modeling, arXiv preprint, arXiv:1604.00100v1 [cs.CL], 2016.
Subit Chakrabarti, Tara Bongiovanni, Jasmeet Judge, Anand
Rangarajan and Sanjay Ranka, Disaggregation of SMAP L3 brightness
temperatures to 9km using kernel machines, arXiv preprint,
arXiv:1601.0535v1 [cs.CV], 2016. Qi Deng, Guanghui Lan and Anand Rangarajan, Randomized block subgradient methods
for convex nonsmooth and stochastic optimization, arXiv
preprint, 1509.04609 [math.OC], September 2015. Yuan Zhou, Anand Rangarajan and Paul
Gader, A spatial compositional model (SCM)
for linear unmixing and endmember uncertainty estimation,
arXiv preprint, 1509.09243 [cs.CV], October 2015. Rana Haber, Anand Rangarajan and
Adrian M. Peter, Discriminative interpolation for
classification of functional data,
European Conference on Machine Learning and Principles and Practice of
Knowledge Discovery in Databases (ECML PKDD), Portugal, 2015. Manu Sethi, Yupeng Yan, Anand
Rangarajan, Ranga Raju Vatsavai and Sanjay Ranka, Scalable machine learning approaches for neighborhood
classification using very high resolution remote sensing
imagery, 21st ACM SIGKDD conference on Knowledge Discovery and Data Mining
(KDD), 2015. Yuan Zhou, Anand Rangarajan and Paul
Gader, A spatial compositional model for
linear unmixing,
IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution
in Remote Sensing (WHISPERS), Japan, 2015. Subit Chakrabarti, Jasmeet Judge, Anand
Rangarajan and Sanjay Ranka, Downscaling microwave brightness temperatures using self regularized regressive models,
Best Student Paper award (2nd place) to
Subit Chakrabarti, IGARSS 2015, arXiv preprint,
arXiv:1501.07683 [cs.CV], 2015. Karthik S. Gurumoorthy and Anand Rangarajan, A Schrödinger formalism for simultaneously computing
the Euclidean distance transform and its gradient density,
Indian Conference on Computer Vision, Graphics and Image Processing
(ICVGIP), (accepted), 2014. Rob Heylen, Paul Scheunders, Anand
Rangarajan and Paul Gader, Nonlinear unmixing
by using non-Euclidean metrics in an unmixing chain, IEEE Journal
of Selected Topics in Applied Earth Observations and Remote Sensing
(JSTARS), 8(6):2655-2664, 2015. Ayan Biswas, David Thompson, Wenbin He, Qi Deng, Chun-Ming Chen, Han-Wei Shen, Raghu Machiraju, and Anand Rangarajan, An uncertainty-driven approach to
vortex analysis using oracle consensus and spatial proximity,
PacificVis 2015, Hangzhou, China, (accepted), 2015. Subit Chakrabarti, Jasmeet Judge, Anand
Rangarajan and Sanjay Ranka, Disaggregation of remotely sensed soil moisture in heterogeneous landscapes using holistic structure-based models,
arXiv preprint, arXiv:1501.07680 [cs.CV], 2015. Adrian Peter, Karthik
S. Gurumoorthy, Mark Moyou and Anand Rangarajan, A new energy minimization
framework and sparse linear system for path planning and shape from shading,
Indian Conference on Computer Vision, Graphics and Image Processing
(ICVGIP), (accepted), 2014. John Corring and Anand
Rangarajan, Shape from phase: An integrated
level set and probability density shape representation,
International Conference on Pattern Recognition (ICPR),
(accepted), 2014. Manu Sethi, Yupeng Yan, Anand
Rangarajan, Ranga Raju Vatsavai and Sanjay Ranka, An efficient computational framework
for labeling large scale spatiotemporal remote sensing datasets, IC3 2014: 635-640. Yan Deng, Anand Rangarajan,
Stephan J. Eisenschenk and Baba Vemuri, A Riemannian framework
for matching point clouds represented by the Schrödinger
distance transform, IEEE Conference on Computer Vision and
Pattern Recognition (CVPR), (accepted), 2014. Pegah Massoudifar, Anand
Rangarajan, Alina Zare and Paul Gader, An
integrated graph cuts segmentation and piecewise convex
unmixing approach for hyperspectral segmentation, IEEE
Workshop on Hyperspectral Image and Signal Processing: Evolution
in Remote Sensing (WHISPERS), (accepted), 2014. Rob Heylen, Paul Scheunders, Anand
Rangarajan and Paul Gader, Nonlinear unmixing by
using non-Euclidean metrics in a linear unmixing chain, IEEE
Workshop on Hyperspectral Image and Signal Processing: Evolution
in Remote Sensing (WHISPERS), (accepted), 2014. Pegah Massoudifar, Anand
Rangarajan and Paul Gader, Superpixel
estimation for hyperspectral imagery, Perception Beyond
the Visible Spectrum (PBVS), An IEEE Computer Vision and Pattern
Recognition (CVPR) Workshop, (accepted), 2014. L. Zhang, Q. Deng. R.
Machiraju, A. Rangarajan, D. Thompson, D.K. Walters and H.-W.
Shen, Boosting techniques for
physics-based vortex detection, Computer Graphics Forum,
33(1):282-293, 2014. Qi Deng, Jeffrey Ho and
Anand Rangarajan, Stochastic coordinate descent for
nonsmooth convex optimization, OPT 2013, A Neural
Information Processing Systems (NIPS) Workshop, 2013. Anand Rangarajan, Revisioning the
unification of syntax, semantics and statistics in shape
analysis, Pattern Recognition Letters, 43:39-46, 2014. Manu Sethi, Anand
Rangarajan and Karthik S. Gurumoorthy, The Schrödinger
distance transform (SDT) for point-sets and curves, IEEE
Conf. on Computer Vision and Pattern Recognition (CVPR),
pp. 198-205, 2012. © IEEE. Karthik S. Gurumoorthy and
Anand Rangarajan, Distance transform gradient
density estimation using the stationary phase approximation,
SIAM Journal on Mathematical Analysis, 44(6): 4250-4273, 2012. ©
SIAM. Ting Chen, Anand
Rangarajan, Stephan J. Eisenschenk and Baba C. Vemuri, Construction of a
neuroanatomical shape complex atlas from 3D MRI brain
structures, NeuroImage, 60(3):1778-1787, 2012. ©
Elsevier. Ajit Rajwade, Anand
Rangarajan and Arunava Banerjee, Image denoising using the higher
order singular value decomposition (supplemental
material), IEEE Trans. Patt. Anal. Mach. Intell., 35(4):
849-862, 2013. © IEEE. Ting Chen, Baba Vemuri,
Anand Rangarajan, and Stephan J. Eisenschenk, Mixture of segmenters with discriminative
regularization and sparse weight selection,
Medical Image Computing and Computer Assisted Intervention
(MICCAI), 3, pp. 595-602, Springer LNCS 6893, 2011. Young Scientist award to Ting Chen. Adrian Peter and Anand
Rangarajan, An information geometry approach
to shape density minimum description length model selection,
IEEE Intl. Conf. Computer Vision (ICCV) Workshops, pp.
1432-1439, 2011. © IEEE. Kittipat Kampa, Jose
Principe, Duangmanee Putthividhya and Anand Rangarajan, Data-driven tree-structured Bayesian network for
image segmentation, IEEE Conf. Acoust. Speech and
Sig. Proc. (ICASSP), pp. 2213-2216, 2012. © IEEE. Karthik S. Gurumoorthy,
Anand Rangarajan and Arunava Banerjee, The Complex Wave Representation of Distance
Transforms,
Energy Minimization Methods in Computer Vision and Pattern
Recognition (EMMCVPR), pp. 413-427, Springer LNCS 6819, 2011. Ajit Rajwade, Anand
Rangarajan and Arunava Banerjee, Using the Higher Order Singular
Value Decomposition (HOSVD) for Video Denoising,
Energy Minimization Methods in Computer Vision and Pattern
Recognition (EMMCVPR), pp. 344-354, Springer LNCS 6819, 2011. Karthik S. Gurumoorthy,
Anand Rangarajan and Arunava Banerjee, A complex exponential Fourier transform approach to
gradient density estimation, Statistics and
Probability Letters, (rejected without review), 2011. Ting Chen, Anand
Rangarajan, Stephan J. Eisenschenk and Baba C. Vemuri, Construction
of Neuroanatomical Shape Complex Atlas from 3D Brain MRI,
Medical Image Computing and Computer Assisted Intervention
(MICCAI), 3, pp. 65-72, Springer LNCS 6363, 2010. Ajit Rajwade, Anand
Rangarajan and Arunava Banerjee, Automated filter parameter selection
using measures of noiseness, Seventh Canadian Conference
on Computer and Robot Vision (CRV), 2010. Ting Chen, Anand Rangarajan
and Baba Vemuri, CAVIAR: Classification via
Aggregated Regression and its application in classifying the
OASIS brain database, IEEE International Symposium on
Biomedical Imaging (ISBI), 2010. Karthik Gurumoorthy, Ajit
Rajwade, Arunava Banerjee and Anand Rangarajan, A Method for
Compact Image Representation using Sparse Matrix and Tensor
Projections onto Exemplar Orthonormal Bases, IEEE
Transactions on Image Processing, 19(2): 322-334, February 2010.
Ajit Rajwade, Arunava
Banerjee and Anand Rangarajan, Image
filtering driven by level curves, Energy
Minimization Methods in Computer Vision and Pattern Recognition
(EMMCVPR), Springer LNCS 5681, 359-372, 2009. Jeffrey Ho, Adrian Peter,
Anand Rangarajan and Ming-Hsuan Yang, An
algebraic
approach to affine registration of point sets,
IEEE International Conference on Computer Vision (ICCV), 2009. Ting Chen, Baba Vemuri,
Anand Rangarajan, and Stephan J. Eisenschenck, Group-wise
point-set registration using a novel CDF-based Havrda-Charvát
Divergence, International Journal of Computer Vision
(IJCV), 86(1):111-124, 2010. Anand Rangarajan and
Karthik S. Gurumoorthy, A Schrödinger wave
equation approach to the eikonal equation: Application to
image analysis, Energy Minimization Methods in
Computer Vision and Pattern Recognition (EMMCVPR), Springer LNCS
5681, 140-153, 2009. Karthik Gurumoorthy and
Anand Rangarajan, A Schrödinger equation for the
fast computation of approximate Euclidean distance functions,
2nd International Conference on Scale Space and Variational
Methods in Computer Vision (SSVM), Springer LNCS 5567, pp.
100-111, 2009. Fei Wang, Tanveer
Syeda-Mahmood, Baba Vemuri, David Beymer and Anand Rangarajan, Closed-form Jensen-Renyi
Divergence for Mixture of Gaussians and Applications to
Group-wise Shape Registration, Medical Image
Computing and Computer Assisted Intervention (MICCAI), Springer
LNCS 5761, 1:648-655, 2009. Hongyu Guo and Anand
Rangarajan, Diffeomorphic
point
matching with applications in biomedical image registration,
International Journal of Tomography and Statistics,
15(F10):42-57, 2010. Karthik Gurumoorthy, Ajit
Rajwade, Arunava Banerjee and Anand Rangarajan, Beyond SVD: Sparse Projections
Onto Exemplar Orthonormal Bases for Compact Image
Representation, 19th International
Conference on Pattern Recognition (ICPR), Best Scientific Paper Award,
2008. Adrian Peter, Anand
Rangarajan, and Jeffrey Ho, Shape L'Âne Rouge: Sliding
wavelets for indexing and retrieval, IEEE Conf. on
Computer Vision and Pattern Recognition (CVPR), 2008. Ajit Rajwade, Arunava
Banerjee and Anand Rangarajan, Probability
Density Estimation using Isocontours and Isosurfaces:
Application to Information Theoretic Image Registration,
IEEE Transactions on Pattern Analysis and Machine Intelligence,
31(3):475-491, March 2009. Code
available (under GPL version 2). Adrian Peter and
Anand Rangarajan, Information Geometry for
Landmark Shape Analysis: Unifying Shape Representation and
Deformation, IEEE Transactions on Pattern Analysis and
Machine Intelligence, 31(2):337-350, February, 2009. Fei Wang, Baba Vemuri,
Anand Rangarajan, and Stephan J. Eisenschenck, Simultaneous
Nonrigid Registration of Multiple Point-Sets and Atlas
Construction, IEEE Transactions on Pattern Analysis
and Machine Intelligence, 30(11):2011-2022, November 2008.
Adrian Peter and
Anand Rangarajan, Maximum Likelihood
Wavelet Density Estimation with Applications to Image and
Shape Matching, IEEE Transactions on Image Processing,
vol. 17, no. 4, pp. 458–468, April 2008. Jeffrey Ho, Ming-Hsuan
Yang, Anand Rangarajan and Baba Vemuri, A
New Affine Registration Algorithm for Matching 2D Point Sets,
Workshop on Applications of Computer Vision (WACV), 2007. Arunabha Roy, Ajay Gopinath
and Anand Rangarajan, Deformable Density Matching
for 3D Non-rigid Registration of Shapes, Medical Image
Computing and Computer Assisted Intervention (MICCAI), Springer
LNCS 4791, 1:942-949, 2007. Santosh Kodipaka, Baba
Vemuri, Anand Rangarajan, Christiana Leonard, Ilona Schmallfuss
and Stephan J. Eisenschenk, Kernel
Fisher Discriminant for Shape-based Classification in
Epilepsy, Medical Image Analysis, 11(1):79-90, 2007
Adrian Peter and
Anand Rangarajan, A New Closed-Form Information
Metric for Shape Analysis, Medical Image Computing and
Computer Assisted Intervention (MICCAI), 2006. Fei Wang, Baba Vemuri and
Anand Rangarajan, Groupwise point pattern registration
using a novel CDF-based Jensen-Shannon Divergence, IEEE
Computer Vision and Pattern Recognition, 2006. Ajit Rajwade, Arunava
Banerjee and Anand Rangarajan, A New Method of Probability
Density Estimation with Application to Mutual Information
Based Image Registration, IEEE Computer Vision and Pattern
Recognition (CVPR), 2006. Adrian Peter and
Anand Rangarajan, Shape matching using
the Fisher-Rao Riemannian metric: Unifying shape
representation and deformation, IEEE International
Symposium on Biomedical Imaging (ISBI), 2006. Ajit Rajwade, Arunava
Banerjee and Anand Rangarajan, Continuous image
representations avoid the histogram binning problem in mutual
information-based image registration, IEEE International
Symposium on Biomedical Imaging (ISBI), 2006. Hongyu Guo, Anand
Rangarajan and Sarang Joshi, Diffeomorphic Point Matching,
Mathematical Models in Computer Vision: The Handbook, 2005. Fei Wang, Baba Vemuri,
Anand Rangarajan, Ilona M. Schmalfuss and Stephan J.
Eisenschenck, Simultaneous registration of multiple
point-sets and atlas construction, European Conference on
Computer Vision (ECCV), 2006. Hongyu Guo, Anand
Rangarajan and Sarang Joshi, 3D diffeomorphic
shape registration using hippocampal datasets, Medical
Image Computing and Computer Assisted Intervention (MICCAI),
2005. Jie Zhang and Anand
Rangarajan, Multimodality image registration
using an extensible information metric and high-dimensional
histogramming, Information Processing in Medical Imaging
(IPMI), 2005. Hongyu Guo, Anand
Rangarajan, Sarang Joshi and Laurent Younes,
A new joint clustering and
diffeomorphism estimation algorithm for non-rigid shape
matching, IEEE Workshop on Articulated and Non-rigid
motion (ANM), 2004. Jie Zhang and Anand
Rangarajan, Affine image registration using
a new information metric, IEEE Conference on
Computer Vision and Pattern Recognition (CVPR), 2004. Hongyu Guo, Anand
Rangarajan, Sarang Joshi and Laurent Younes, Non-rigid
registration
of shapes via diffeomorphic point matching, IEEE
International Symposium on Biomedical Imaging (ISBI), (in
press), 2004. Jie Zhang and Anand
Rangarajan, A unified feature-based
registration method for multimodality images, IEEE
International Symposium on Biomedical Imaging (ISBI), (in
press), 2004. Jie Zhang and Anand
Rangarajan, Bayesian
Multimodality
Non-rigid image registration via conditional density
estimation, Information Processing in Medical
Imaging (IPMI), Springer LNCS 2732, 499-512, 2003. Anand Rangarajan, James
Coughlan and Alan Yuille, A Bayesian network framework for
relational shape matching, International
Conference on Computer Vision (ICCV), volume I, pages 671-678,
IEEE Press, 2003. Haili Chui, Jie Zhang and
Anand Rangarajan,
Unsupervised learning of an atlas from unlabeled point-sets,
IEEE Trans. Patt. Anal. Mach. Intell, 26(2):160-173, 2004. Code
available here. Haili Chui, Larry Win,
Robert Schultz, Jim Duncan and Anand Rangarajan, A unified non-rigid
feature registration method for brain mapping,
Medical Image Analysis, 7:112-130, 2003. Haili Chui and Anand
Rangarajan, A
new point matching algorithm for non-rigid registration,
Computer Vision and Image Understanding (CVIU), 89:114-141,
2003. Code available here. Alan Yuille and Anand
Rangarajan, The
Concave-Convex Procedure (CCCP), Neural Computation,
15:915-936, 2003. Haili Chui and Anand
Rangarajan, Learning an
atlas from unlabeled point-sets, IEEE Workshop on
Mathematical Methods in Biomedical Image Analysis (MMBIA),
179-186, 2001. Anand Rangarajan, Haili
Chui and Eric Mjolsness A
relationship between spline-based deformable models and
weighted graphs in non-rigid matching, IEEE Computer
Vision and Pattern Recognition (CVPR), volume I, 897-904, 2001.
Anand Rangarajan Learning matrix space image
representations, Energy Minimization Methods in
Computer Vision and Pattern Recognition (EMMCVPR), Springer LNCS
2134:153-168, 2001. Anand Rangarajan and Alan
Yuille MIME: Mutual
information minimization and entropy maximization for
Bayesian belief propagation, Neural Information
Processing Systems (NIPS), 14, pp 873-880, MIT Press, 2002. Alan Yuille and Anand
Rangarajan The Convex-Concave
Computational Procedure (CCCP), Neural Information
Processing Systems (NIPS), MIT Press, Cambridge, MA, 1033-1040,
2002. Haili Chui and Anand
Rangarajan A new algorithm
for non-rigid point matching, IEEE Conference on
Computer Vision and Pattern Recognition (CVPR), volume II,
44-51, Best Paper, Honorable Mention, 2000. Haili Chui and Anand
Rangarajan, A feature registration framework
using mixture models, IEEE Workshop on
Mathematical Methods in Biomedical Image Analysis (MMBIA),
190-197, 2000. Anand Rangarajan, Haili
Chui and Eric Mjolsness, A new distance measure for
non-rigid image matching, Energy Minimization
Methods in Computer Vision and Pattern Recognition (EMMCVPR),
Edwin Hancock and Marcello Pelillo, editors, pages pages
237-252, Springer, 1999. Haili Chui, James Rambo,
James Duncan, Robert Schultz and Anand Rangarajan, Registration of cortical anatomical
structures with robust 3D point matching,
Information Processing in Medical Imaging, Attila Kuba, Martin
Samal and Andrew Todd-Pokropek, editors, pages 168-181,
Springer, 1999. Anand Rangarajan, Haili
Chui and James S. Duncan, Rigid
point feature registration using mutual information,
Medical Image Analysis, 3(4):425-440, 1999. Anand Rangarajan, Haili
Chui and Fred L. Bookstein, The
Softassign Procrustes Matching Algorithm,
Information Processing in Medical Imaging, James Duncan and Gene
Gindi, editors, pages 29-42, Springer, 1997. Anand Rangarajan and Eric
Mjolsness, A Lagrangian Relaxation
Network for Graph Matching, IEEE Transactions on
Neural Networks, 7(6):1365-1381, 1996. Steven Gold and Anand
Rangarajan, A Graduated Assignment
Algorithm for Graph Matching, IEEE Transactions on
Pattern Analysis and Machine Intelligence, 18(4):377-388, April
1996. Steven Gold, Anand
Rangarajan and Eric Mjolsness, Learning
with
Preknowledge: Clustering with point- and graph-matching
distance measures, Neural Computation, 8(4):787-804,
May 1996. Anand Rangarajan, Haili
Chui, Eric Mjolsness, Suguna Pappu, Lila Davachi, Patricia S.
Goldman-Rakic and James S. Duncan, A
Robust Point Matching Algorithm for Autoradiograph Alignment,
Medical Image Analysis, 1(4):379-398, 1997. Anand Rangarajan, Eric
Mjolsness, Suguna Pappu, Lila Davachi, Patricia S. Goldman-Rakic
and James S. Duncan, A Robust Point
Matching Algorithm for Autoradiograph Alignment,
Visualization in Biomedical Computing (VBC), K. H. Hohne and R.
Kikinis editors, pp. 277-286, 1996. Suguna Pappu, Steven Gold
and Anand Rangarajan, A framework
for non-rigid matching and correspondence, Advances
in Neural Information Processing Systems 8, pp. 795-801, 1996. Steven Gold, Anand
Rangarajan, Chien-Ping Lu, Suguna Pappu and Eric Mjolsness, New Algorithms for 2D and 3D Point
Matching: Pose Estimation and Correspondence,
Pattern Recognition, 31(8):1019-1031, 1998. Gene Gindi, Anand
Rangarajan and George Zubal, Atlas-Guided
Segmentation of Brain Images via Optimizing Neural Networks,
Proc. SPIE Biomedical Image Processing IV, February, 1993.
Tomographic Reconstruction:
Sangeetha Somayajula,
Christos Panagiotou, Anand Rangarajan, Quanzheng Li, Simon R.
Arridge, Richard M. Leahy, PET image reconstruction using
information-theoretic anatomical priors, IEEE
Transactions on Medical Imaging, 30(3):537-549, 2010. Lili Zhou, Sangeetha Somayajula, Anand
Rangarajan and Richard M. Leahy, PET image reconstruction
using anatomical information through mutual information
based priors: A scale space approach, IEEE
International Symposium on Biomedical Imaging (ISBI), pp.
165-168, 2007. Parmeshwar Khurd, Lili
Zhou, Anand Rangarajan and Gene Gindi, Aperture Optimization in Emission Imaging Using Optimal LROC Observers,
IEEE Medical Imaging Conference (MIC), 2006. Ing-Tsung Hsiao, Anand
Rangarajan, Parmeshwar Khurd and Gene Gindi, An overview of fast
convergent ordered-subsets reconstruction methods for
emission tomography based on the incremental EM algorithm,
Nuclear Instruments and Methods in Physics Research A, vol 569,
pp. 429-433, Dec 2006 Ing-Tsung Hsiao, Anand
Rangarajan, Parmeshwar Khurd and Gene Gindi, Fast, Globally Convergent
Reconstruction in Emission Tomography using COSEM, an
Incremental EM Algorithm, IEEE Trans. Medical
Imaging, (rejected), 2004. Anand Rangarajan,
Parmeshwar Khurd, Ing-Tsung Hsiao and Gene Gindi, Convergence Proofs for the COSEM-ML and COSEM-MAP
Algorithms, Technical Report,
MIPL-03-01, Dec.
2003. Ing-Tsung Hsiao, Anand
Rangarajan, Parmeshwar Khurd and Gene Gindi, A New, Fast, Relaxation-free
Convergent Ordered Subset Algorithm for Emission Tomography,
IEEE International Symposium on Biomedical Imaging, 2004.
Parmeshwar Khurd ,
Ing-Tsung Hsiao, Anand Rangarajan, and Gene Gindi, A Globally Convergent Regularized
Ordered Subset EM Algorithm for List Mode Reconstruction,
IEEE Trans. Nuclear Science, (submitted), 2004. Ing-Tsung Hsiao, Anand
Rangarajan, Parmeshwar Khurd and Gene Gindi, An Accelerated
Convergent Ordered Subsets Algorithm for Emission Tomography,
Physics in Medicine and Biology, (submitted), 2004. Ing-Tsung Hsiao, Anand
Rangarajan and Gene Gindi, A
new convergent MAP reconstruction algorithm for emission
tomography using ordered subsets and separable surrogates,
IEEE International Symposium on Biomedical Imaging (ISBI), 2002.
Ing-Tsung Hsiao, Anand
Rangarajan and Gene Gindi, A
smoothing prior with embedded positivity constraint for
tomographic reconstruction, Symposium on Fully 3D
reconstruction, 2001. Ing-Tsung Hsiao, Anand
Rangarajan and Gene Gindi, A new convex
edge-preserving median prior with applications to tomography,
IEEE Trans. Med. Imaging, 22(5):580-585, 2004. Ing-Tsung Hsiao, Anand
Rangarajan and Gene Gindi, Joint MAP Bayesian
tomographic reconstruction with a Gamma-mixture prior,
IEEE Trans. Image Proc. 11(12):1466-1477, 2002. Ing-Tsung Hsiao, Anand
Rangarajan and Gene Gindi, Bayesian
reconstruction
for transmission tomography using deterministic annealing,
Journal of Electronic Imaging, 2(1):7-16, 2003. Anand Rangarajan,
Ing-Tsung Hsiao and Gene Gindi, A
Bayesian joint mixture framework for the integration of
anatomical information in functional image reconstruction,
Journal of Mathematical Imaging and Vision, 12:199-217, 2000. Anand Rangarajan, Soo-Jin
Lee and Gene Gindi, Mechanical
Models as Priors in Bayesian Tomographic Reconstruction,
Maximum Entropy and Bayesian Methods, K. M. Hanson and R. N.
Silver editors, pp. 117-124, 1996. Soo-Jin Lee, Anand
Rangarajan and Gene Gindi, Bayesian
Image Reconstruction in SPECT Using Higher Order Mechanical
Models as Priors, IEEE Transactions on Medical
Imaging, 14(4):669-680, December 1995. Soo-Jin Lee, Gene Gindi,
George Zubal and Anand Rangarajan, Using
Ground
Truth data to design priors in Bayesian SPECT Reconstruction,
Information Processing in Medical Imaging, pp. 27-39, 1995. Soo-Jin Lee, Anand
Rangarajan and Gene Gindi, A
Comparative Study of the Effects of Using Higher Order
Mechanical Priors in SPECT Reconstruction, IEEE
Nuclear Science Symposium and Medical Imaging Conferences, pages
1696-1700, November 1994. Gene Gindi and Anand
Rangarajan, What can SPECT learn
from Autoradiography?, IEEE Nuclear Science
Symposium and Medical Imaging Conferences, pages 1715-719,
November 1994. Gene Gindi, Anand
Rangarajan, Mindy Lee, P. J. Hong and George Zubal, Bayesian Reconstruction for Emission
Tomography via Deterministic Annealing, Information
Processing in Medical Imaging, H. H. Barrett and A. F. Gmitro,
editors, LNCS 687, pp. 322-338, Springer-Verlag, 1993 .
Neural Networks and Combinatorial Optimization:
Anand Rangarajan, Self Annealing and Self
Annihilation: Unifying deterministic annealing and
relaxation labeling, Pattern Recognition
33:635-649, 2000. Anand Rangarajan, Steven
Gold and Eric Mjolsness, A novel
optimizing network architecture with applications,
Neural Computation, 8(5):1041-1060, 1996. Anand Rangarajan, Self Annealing: Unifying
deterministic annealing and relaxation labeling,
Energy Minimization Methods in Computer Vision and Pattern
Recognition (EMMCVPR), M. Pelillo and E. Hancock, editors, (in
press), Springer, 1997. Anand Rangarajan, Alan
Yuille, Steven Gold and Eric Mjolsness, A convergence proof for the softassign
quadratic assignment algorithm, Advances in Neural
Information Processing Systems 9, M. Mozer, M. Jordan and T.
Petsche, editors, pages 620-626, MIT Press, 1997. Anand Rangarajan, Alan
Yuille, and Eric Mjolsness, Convergence
properties of the softassign quadratic assignment algorithm,
Neural Computation, 11:1455-1474, 1999. Steven Gold and Anand
Rangarajan, Softmax to Softassign:
Neural Network Algorithms for Combinatorial Optimization,
Journal of Artificial Neural Networks, pages 381-399, Aug. 1996. Eric Mjolsness, Anand
Rangarajan and Charles Garrett, A neural net for the
reconstruction of multiple curves from a visual grammar,
International Joint Conference on Neural Networks (IJCNN), vol.
1, pp. 615-620, 1991.
Continuation Methods and Markov Random Fields:
Anand Rangarajan and Rama
Chellappa, Markov random field
models in image processing, The Handbook of Brain
Theory and Neural Networks, M. A. Arbib, editor, pp. 564-567,
The MIT Press, 1995. Michael J. Black and
Anand Rangarajan, On the unification
of line processes, outlier rejection and robust statistics
with applications in early vision, International
Journal of Computer Vision, 19(1):57-91, 1996. Anand Rangarajan, Rama
Chellappa and B. S. Manjunath, Markov random fields and neural
networks with applications to early vision problems,
Artificial Neural Networks and Statistical Pattern Recognition:
Old and New Connections, I. K. Sethi and A. K. Jain, editors,
pp. 155-174, Elsevier Science Press, 1991. Anand Rangarajan and Rama
Chellappa, Generalized
graduated nonconvexity algorithm for maximum a posteriori
image estimation, 10th International
Conference on Pattern Recognition (ICPR), vol. 2, pp. 127-133,
1990. Older Work:
B. Yegnanarayana, J.
Sreekanth and Anand Rangarajan, Waveform estimation
using group delay processing, IEEE Trans. Acoust.
Speech and Signal Proc., 33(4):832-836, Aug. 1985.
Notes:
Anand Rangarajan, Tutorial on the EM algorithm