Authors:
David Feltell
and
Li Bai
Affiliation:
School of Computer Science & IT, Nottingham University, United Kingdom
Keyword(s):
Level Set, Multi Agent Clustering, Image Segmentation.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
Abstract:
This paper presents a novel 3D brain segmentation method based on level sets and bio-inspired methodologies. Level set segmentation methods, although highly promising, require manual selection of seed positions and thereshold parameters, along with manual reinitialisation to a new level set surface for each candidate region. Here, the use of swarm intelligent mechanisms is used to provide all the statistical data and sample points required, allowing automatic initialisation of multiple level set solvers. This is shown by segmentation of white matter, grey matter and cerebro-spinal fluid in a simulated T1 MRI scan, followed by direct comparison between a commercial level application - FMRIB’s FAST - and the ground truth anatomical model.