Share Email Print
cover

Proceedings Paper

Fuzzy c-means approach to tissue classification in multimodal medical imaging
Author(s): S. Banerjee; D. P. Mukherjee; D. Dutta Majumdar; S. S. Kohli; Vinod K. Mishra
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

In this note, we present our endeavors to segment same cross-sections of the human brain obtained from the two modalities -- x-ray computed tomography (CT) and magnetic resonance imaging (MRI) -- using the fuzzy c-means technique developed by Bezdek. The two advantages of the technique are that it is unsupervised and is robust to missing and noisy data. Attempts at integrating the images from these two modalities are also mentioned.

Paper Details

Date Published: 4 March 1996
PDF: 6 pages
Proc. SPIE 2664, Applications of Artificial Neural Networks in Image Processing, (4 March 1996); doi: 10.1117/12.234263
Show Author Affiliations
S. Banerjee, Indian Statistical Institute (India)
D. P. Mukherjee, Indian Statistical Institute (India)
D. Dutta Majumdar, Indian Statistical Institute (India)
S. S. Kohli, Government of India (India)
Vinod K. Mishra, Government of India (India)


Published in SPIE Proceedings Vol. 2664:
Applications of Artificial Neural Networks in Image Processing
Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

© SPIE. Terms of Use
Back to Top