Title: Segmentation of liver computed tomography images using dictionary-based snakes

Authors: N. Shanila; R.S. Vinod Kumar; R. Ramya Ravi

Addresses: Department of Electronics and Communication Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Kanyakumari, Tamil Nadu, India ' Department of Electronics and Communication Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Kanyakumari, Tamil Nadu, India ' Department of Electronics and Communication Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Kanyakumari, Tamil Nadu, India

Abstract: In medical research, segmentation can be used in separating different tissues from each other, through extracting and classifying the features. Segmentation of liver from computed tomography (CT) and magnetic resonance imaging (MRI) is a challenging task. Many image segmentation methods have been used in medical applications. In addition to the briefing of the need, concept and advantages of a few liver segmentation methods, this paper introduces a novel approach for the segmentation of liver computed tomography images using dictionary snakes. The performance of the proposed method is quite satisfactory.

Keywords: image processing; liver segmentation; computed tomography; pre-processing; active contour; snakes; dictionary snakes; segmentation.

DOI: 10.1504/IJBET.2022.124188

International Journal of Biomedical Engineering and Technology, 2022 Vol.39 No.3, pp.283 - 296

Received: 11 Jan 2019
Accepted: 05 Jul 2019
Published online: 18 Jul 2022 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article