Use of chaos concept in medical image segmentation

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...

Full description

Saved in:
Bibliographic Details
Published inComputer methods in biomechanics and biomedical engineering. Vol. 1; no. 1; pp. 28 - 36
Main Author Dakua, Sarada Prasad
Format Journal Article
LanguageEnglish
Published Taylor & Francis Group 01.03.2013
Subjects
chaos theory
computed tomography
image segmentation
magnetic resonance
Online AccessGet full text
ISSN2168-1163
2168-1171
DOI10.1080/21681163.2013.765709

Cover

More Information
Summary: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.
ISSN:2168-1163
2168-1171
DOI:10.1080/21681163.2013.765709