By Topic

Image segmentation and registration techniques for MR-Guided Liver Cancer Surgery

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Yen-Wei Chen ; Electron. & Inf. Eng. Sch., Central South Univ. of Forestry & Tech., Changsha, China ; Katsumi Tsubokawa ; Amir H. Foruzan ; Shigehiro Morikaw
more authors

Recently a growing interest has been seen in minimally invasive treatments with open configuration magnetic resonance (Open-MR) scanners. Because of the lower magnetic field (0.5T) and various different surgical conditions, sometimes tumors can not be visualized clearly on Open-MR volumes. Combining of CT volumes acquired before surgery, it is possible to identify the tumor's location by application of registration techniques. In this paper, we proposed a non-rigid registration method combined with a semi-automatic liver segmentation method for MR-Guided Liver Cancer Surgery. We first propose a robust method using K-means clustering and graph cut to segment liver from low contrast open MR images and then a free-form deformation based non-rigid registration method is applied to the segmented livers.

Published in:

Mechatronics and Embedded Systems and Applications (MESA), 2012 IEEE/ASME International Conference on

Date of Conference:

8-10 July 2012