Interfacial gradient priorsbased geodesic geometric flows for 3D medical image segmentation

Purpose The 3D medical image segmentation is a really difficult problem. The purpose of this paper is to present a novel segmentation method for cases that some regions of interest to be segmented from 3D medical images have strong similarities such as gradient between adjacent slides. Designmethodo...

Full description

Saved in:
Bibliographic Details
Published inCompel Vol. 29; no. 2; pp. 505 - 514
Main Authors Hao, Jiasheng, Shen, Yi, Xu, Hongbing, Zou, Jianxiao
Format Journal Article
LanguageEnglish
Published Emerald Group Publishing Limited 09.03.2010
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Purpose The 3D medical image segmentation is a really difficult problem. The purpose of this paper is to present a novel segmentation method for cases that some regions of interest to be segmented from 3D medical images have strong similarities such as gradient between adjacent slides. Designmethodologyapproach This method brings gradient characteristics of the adjacentsegmented slide, called interfacial gradient priors, into the slide waiting for segmentation and to help the contour converge to actual boundary more accurately. Findings This method will improve the stopping criterion of curve evolution through introduction of adjacent slide's prior information into edge detection function, so that the leakage phenomena that exists in geometric active contour model when discontinuous or weak edges appear is reduced. Originalityvalue Introducing adjacent slide's priors improves the precision and stability of geodesic geometric flows in 3D medical image segmentation.
Bibliography:href:03321641011014968.pdf
istex:D986EC1C4342D82F8C095B1A5FCF5B91756375C9
filenameID:1740290222
ark:/67375/4W2-6PGDX2W7-D
original-pdf:1740290222.pdf
ISSN:0332-1649
2054-5606
DOI:10.1108/03321641011014968