A New Scheme for Automatic Initialization of Deformable Models

Abstract

This paper presents a novel scheme for automatic initialization for all types of deformable models. Our method is able to automatically generate a close-to-boundary initialization which is independent of the subsequent segmentation process. Therefore, our method enables different types of deformable models achieve more accurate and robust results. Topographic independent component analysis (TICA) based feature extraction technique is presented for learning a representation from a set of un-labeled image patches. During learning, a topographic map of basis components emerge. An intelligent contour generation procedure is also proposed. Experimental results on abdominal CT images demonstrate the potential of our approach.