Data Entry: Please note that the research database will be replaced by UNIverse by the end of October 2023. Please enter your data into the system https://universe-intern.unibas.ch. Thanks
Variational Segmentation of the White and Gray Matter in the Spinal Cord using a Shape Prior
Editor(s)
Yao , Jianhua; Vrtovec, Tomaž; Zheng, Guoyan; Frangi, Alejandro; Glocker , Ben; Li , Shuo
Book title (Conference Proceedings)
4th MICCAI Workshop and Challenge: Computational Methods and Clinical Applications for Spine Imaging (CSI)
Place of Conference
Athen
Publisher
Springer
Place of Publication
Berlin
Pages
26-37
ISSN/ISBN
978-3-319-55049-7 ; 978-3-319-55050-3
Abstract
Segmenting the inner structure of the spinal cord on magnetic resonance (MR) images is difficult because of poor contrast between white and gray matter (WM/GM). We present a variational formulation to automatically detect cerebrospinal fluid and WM/GM. The segmentation results are obtained by continuous cuts combined with a shape prior. Intensity-based segmentation guarantees high accuracy while the shape prior aims at precision. We tested the algorithm on a set of MR images with visual WM/GM contrast and evaluated it w.r.t. manual GM segmentations. The automated GM segmentations are on a par with the manual results.
