Fuzzy c-means approach to tissue classification in multimodal medical imaging

S. Banerjee; D. P. Mukherjee; D. Dutta Majumdar; S. S. Kohli; Vinod K. Mishra

doi:10.1117/12.234263

4 March 1996 Fuzzy c-means approach to tissue classification in multimodal medical imaging

S. Banerjee, D. P. Mukherjee, D. Dutta Majumdar, S. S. Kohli, Vinod K. Mishra

Proceedings Volume 2664, Applications of Artificial Neural Networks in Image Processing; (1996) https://doi.org/10.1117/12.234263
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States

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.

Citation Download Citation

S. Banerjee, D. P. Mukherjee, D. Dutta Majumdar, S. S. Kohli, and Vinod K. Mishra "Fuzzy c-means approach to tissue classification in multimodal medical imaging", Proc. SPIE 2664, Applications of Artificial Neural Networks in Image Processing, (4 March 1996); https://doi.org/10.1117/12.234263

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