A Coupled Minimization Problem for Medical Image Segmentation with Priors |
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Authors: | Yunmei Chen Feng Huang Hemant D. Tagare Murali Rao |
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Affiliation: | (1) Department of Mathematics, University of Florida, Gainesville, FL, 32611;(2) Invivo Corporation, Gainesville, FL, 32608;(3) Department of Diagnostic Radiology, Department of Electrical Engineering, Yale University, New Haven, CT, 06520 |
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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. |
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Keywords: | segmentation registration shape prior intensity prior mutual information of image geometry variational method |
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