By Topic

Representative line detection algorithm with fuzzy inference and its application to segmentation of CT knee images

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
$31 $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

6 Author(s)
Shibata, M. ; Himeji Inst. of Technol., Graduate Sch. of Eng., Himeji, Japan ; Kobashi, S. ; Kondo, K. ; Hata, Y.
more authors

We propose a new algorithm called the representative line detection algorithm which embeds physician knowledge with fuzzy if-then rules. The algorithm detects the representative line of the region of interest (ROI). The representative line can show the rough location and shape. We first consider the representative line which consisted of some nodes. These nodes are then automatically detected by tracking the most suitable direction from the starting node. To evaluate this algorithm, it is applied to segmentation of the meniscus from CT knee images. The experimental results of six normal subjects showed that the representative line detection algorithm could express the center line of the meniscus, and could lead to detection of successful segmentation of the menisci.

Published in:

Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on  (Volume:5 )

Date of Conference:

18-22 Nov. 2002