A New Framework of Multiphase Segmentation and Its Application to Partial Volume Segmentation. (3rd April 2011)

• Record Type: Journal Article
• Authors: Chen, Fuhua; Chen, Yunmei; Tagare, Hemant D.
• Other Names: Di Nola Antonio Academic Editor.
• Is Part Of: Applied computational intelligence and soft computing. Volume 2011(2011)
• Publication Date: 2011-04-03
• Subjects: Computational intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• DOI: 10.1155/2011/786369
• Languages: English
• ISSNs: 1687-9724

Abstract

Abstract : We proposed a novel framework of multiphase segmentation based on stochastic theory and phase transition theory. Our main contribution lies in the introduction of a constructed function so that its composition with phase function forms membership functions. In this way, it saves memory space and also avoids the general simplex constraint problem for soft segmentations. The framework is then applied to partial volume segmentation. Although the partial volume segmentation in this paper is focused on brain MR image, the proposed framework can be applied to any segmentation containing partial volume caused by limited resolution and overlapping.