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My research interests are medical imaging, neural networks, computer vision, combinatorial optimization and the scientific study of consciousness.
Objective functions defined on mixed (binary and continuous) variables frequently arise in a Bayesian maximum a posteriori (MAP) context. My work focuses on formulating such objectives and then designing deterministic annealing, continuation methods for optimizing these objective functions. The application areas are medical image matching, tomographic reconstruction in medical imaging, and neural networks for combinatorial optimization.
Associate Research
Scientist, Departments of Diagnostic Radiology and Computer Science,
Yale University. (1992-1995) Postdoctoral Associate,
Departments of Diagnostic Radiology and Computer Science, Yale University.
(1991-1992) Graduate Research Assistant,
Signal and Image Processing Institute, Department of Electrical Engineering,
University of Southern California. (1984-1990) Bachelor of Technology,
Electronics Engineering, Indian Institute of Technology (IIT), Madras,
India. (1979-1984)
Haili Chui and
Anand Rangarajan
A new
algorithm for non-rigid point matching
, IEEE Conference on Computer Vision and Pattern
Recognition (CVPR), (accepted), 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, (in press), 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, 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. 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,
in press, August 1997. 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
, in press, Pattern Recognition, 1997. 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.
Rotating Stack
Cut through Stack Anand Rangarajan, Ing-Tsung
Hsiao and Gene Gindi, A joint mixture framework
for the integration of anatomical information in functional image
reconstruction,
Journal of Mathematical Imaging and Vision (submitted), 1999. 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 . Arun Jagota, Anand
Rangarajan and Xin Wang, Cycle-free dynamics
of a cluster-competitive net,
Discrete Applied Mathematics (in press), 1999. Anand Rangarajan, Self
Annealing and Self Annihilation:
Unifying deterministic annealing and relaxation labeling,
Pattern Recognition (in press), 1999. 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,
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
,
submitted to Neural Computation, 1998. Steven Gold and Anand
Rangarajan, Softmax to Softassign: Neural
Network Algorithms for Combinatorial Optimization, Journal of
Artificial Neural Networks, pages 381-399, Aug. 1996. 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, Book
Review of "The Embodied Mind: Cognitive Science and Human Experience",
by Francisco Varela, Evan Thompson and Eleanor Rosch, MIT Press, 1991. Anand Rangarajan,
Towards a science of consciousness and
towards a consciousness of science (abstract),
in Towards a Science of Consciousness, Tucson 3, 1998. Anand Rangarajan,
Summary of Gregg Rosenberg's Ph.D. thesis,
A Place for Consciousness: Probing the deep structure of
the natural world, 1999. Anand Rangarajan,
A Dual-Aspect Panpsychist Critique of Emergentist,
Quantum and Wilber's Holonic Theories of Consciousness, in
Towards a Science of Consciousness, Tucson 4, 2000. Anand Rangarajan,
Tutorial on the EM algorithm,
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anand@noodle.med.yale.edu
Snail mail address: Image Processing and Analysis Group, Department of Diagnostic Radiology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520-8042. Ph: (203) 785 7294, Fax: (203) 737 4273, Secretary: (203) 785 2427