A Coupled Minimization Problem for Medical Image Segmentation with Priors

Authors:
Yunmei Chen;Feng Huang;Hemant D. Tagare;Murali Rao
Affiliations:
Department of Mathematics, University of Florida, Gainesville 32611;Invivo Corporation, Gainesville 32608;Department of Diagnostic Radiology, Department of Electrical Engineering, Yale University, New Haven 06520;Department of Mathematics, University of Florida, Gainesville 32611
Venue:
International Journal of Computer Vision
Year:
2007

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Abstract

We present a coupled minimization problem for image segmentation using prior shape and intensity profile. One part of the model minimizes a shape related energy and the energy of geometric active contour with a parameter that balances the influence from these two. The minimizer corresponding to a fixed parameter in this minimization gives a segmentation and an alignment between the segmentation and prior shape. The second part of this model optimizes the selection of the parameter by maximizing the mutual information of image geometry between the prior and the aligned novel image over all the alignments corresponding to different parameters in the first part. By this coupling the segmentation arrives at higher image gradient, forms a shape similar to the prior, and captures the prior intensity profile. We also propose using mutual information of image geometry to generate intensity model from a set of training images. Experimental results on cardiac ultrasound images are presented. These results indicate that the proposed model provides close agreement with expert traced borders, and the parameter determined in this model for one image can be used for images with similar properties.