Computer-Aided Diagnosis (CAD) systems for pathologists can act as an intelligent digital assistant supporting automated grading and morphometric-based discovery of tissue features that are important in cancer diagnosis and patient prognosis. Automated image segmentation is an essential component of computer-based grading in CAD. We describe a novel tissue segmentation algorithm using local feature-based multiphase active contours in a globally convex formulation. By decomposing the image into intensity and chromaticity channels we utilize multiple feature based fitting terms to drive the active contour evolution for effective stromal-epithelial separation. Experimental results using the Stanford Tissue MicroArray (TMA) database shows promising stromal/epithelial superpixel segmentation.
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