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o Recovery of Soft Tissue Object Deformation using Biomechanical Models

Xenophon Papademetris, Pengchgen Shi, Donald P. Dione, Albert J. Sinusas and R. Todd Constable and James S. Duncan.
Technical Report 1999-01. Image Processing and Analysis Labortory, Dept. of Diagnostic Radiology, Yale University New Haven CT.

This is the longer version of the IPMI paper by the same name.

Abstract

The estimation of soft tissue deformation from 3D image sequences is an important problem in a number of fields such as diagnosis of heart disease and image guided surgery. In this paper we describe a methodology for using biomechanical material models, within a Bayesian framework which allows for proper modeling of image noise, in order to estimate these deformations. The resulting partial differential equations are discretized and solved using the finite element method. We demonstrate the application of this method to estimating strains from sequences of in-vivo left ventricular MR images, where we incorporate information about the fibrous structure of the ventricle. The deformation estimates obtained exhibit similar patterns with measurements obtained from more invasive techniques, used as a gold standard.

BibTeX entry 

@TECHREPORT{techPapademetris99,
author = "X. Papademetris and P. Shi and D. P. Dione and
	  A. J. Sinusas  and R. T. Constable and J.S. Duncan ",
title = "Recovery of Soft Tissue Object Deformation from 3D Image Sequences 
         using Biomechanical Models",
institution= "Image Processing and Analysis Group, 
              Dept. of Diagnostic Radiology, Yale University",
year  = " 1999",
number = "1999-01",
month = " March "}

o Estimation of Motion Boundary Location and Optical Flow using Dynamic Programming

Xenophon Papademetris and Peter N. Belhumeur.
Proceedings of IEEE International Conference on Image Processing, September 1996.

An extended version can be found as o Technical Report 9607,
Center for Systems Science, Department of Electrical Engineering, Yale University, June 1996.

Abstract

We present a new method for the estimation of optical flow which uses a dynamic programming-based algorithm to simultaneously detect the presence of motion boundaries and to estimate optical flow. This allows for more accurate estimation of the motion field near discontinuities. We present results from both synthetic and real image sequences which compare favorably with results produced by other methods. Keywords: Optical Flow, Motion Boundaries, Dynamic Programming.

BibTeX entries

@INPROCEEDINGS{xPapademetris96,
	author = "X. Papademetris and P. N. Belhumeur",
	title = "Estimation of Motion Boundary Location and 
	         Optical Flow using Dynamic Programming",
        year  = " 1996",
	booktitle = "Proc. Int. Conf. on Image Processing",
        address = "Lausagne, Switzerland""

@TECHREPORT{tech:Papademetris96,
	author = "X. Papademetris and P. N. Belhumeur",
	title = "Estimation of Motion Boundary Location and  
                 Optical Flow using Dynamic Programming",
        institution= "Center for Systems Science,
                      Dept. of Elec. Engineering , Yale University",
        year  = " 1996",
        number = "9607",
        month = " June "}

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