NDLI: Tissue classification for MRI of thigh using a modified FCM method

Content Provider	IEEE Xplore Digital Library
Author	Kang, H. Pinti, A. Vermeiren, L. Taleb-Ahmed, A. Zeng, X.
Copyright Year	2007
Description	Author affiliation: Univ. de Valenciennes - Le Mont Houy, Valenciennes (Kang, H.)
Abstract	Fuzzy C-means (FCM) has been frequently used to image segmentation in order to separate objects. The most used segmentation attribute is grey level of pixels. Nevertheless, this method can not identify complex image objects because grey level can not take into account all visual information. This paper describes a modified FCM method for tissue classification which integrates separation and fusion operation of partition tree with expert knowledge. Our method has been applied to 26 MRI (Magnetic Resonance Imaging) images of thigh for localizing four main anatomical tissues: muscle, adipose tissue, cortical bone, and spongy bone. A testing dataset of 6500 representative points has been created by an expert. Using our method, we obtain a high classification rate (95.73%) in the test dataset, which largely improved the classification results obtained from existing methods.
Starting Page	5579
Ending Page	5584
File Size	629384
Page Count	6
File Format	PDF
ISBN	9781424407873
ISSN	1557170X
DOI	10.1109/IEMBS.2007.4353611
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-22
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Magnetic resonance imaging Thigh Image segmentation Laboratories Pixel Muscles Cancellous bone Classification tree analysis Testing Radio frequency
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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