Abstract & Overview
Despite its long track record, segmentation in medical image computing still remains an active field of research, largely due to the complexities of in-vivo anatomical structures, cross-subject and cross-modality variations. Clinically, it has many benefits for effective patient management, both in terms of pre-operative planning and post-operative assessment of the efficacy of therapeutic procedures. Research efforts are focused on novel, clinician friendly, robust and fast segmentation methodologies. In this paper, we present a novel algorithm for efficient segmentation based on Chaotic theory; the preliminary results show the potential of the proposed technique.