Super-resolved multi-channel fuzzy segmentation of MR brain images

Ying Bai; Xiao Han; Dzung L. Pham; Jerry L. Prince

doi:10.1117/12.595357

29 April 2005 Super-resolved multi-channel fuzzy segmentation of MR brain images

Ying Bai, Xiao Han, Dzung L. Pham, Jerry L. Prince

Proceedings Volume 5747, Medical Imaging 2005: Image Processing; (2005) https://doi.org/10.1117/12.595357
Event: Medical Imaging, 2005, San Diego, California, United States

Abstract

We propose a new fuzzy segmentation framework that incorporates the idea of super-resolution image reconstruction. The new framework is designed to segment data sets comprised of orthogonally acquired magnetic resonance (MR) images by taking into account their different system point spread functions. Formulating the reconstruction within the segmentation framework improves its robustness and stability, and makes it possible to incorporate multispectral scans that possess different contrast properties into the super-resolution reconstruction process. Our method has been tested on both simulated and real 3D MR brain data.

Citation Download Citation

Ying Bai, Xiao Han, Dzung L. Pham, and Jerry L. Prince "Super-resolved multi-channel fuzzy segmentation of MR brain images", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); https://doi.org/10.1117/12.595357

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