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Proceedings Paper

Super-resolved multi-channel fuzzy segmentation of MR brain images
Author(s): Ying Bai; Xiao Han; Dzung L. Pham; Jerry L. Prince
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Paper 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.

Paper Details

Date Published: 29 April 2005
PDF: 10 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.595357
Show Author Affiliations
Ying Bai, Johns Hopkins Univ. (United States)
Xiao Han, Johns Hopkins Univ. (United States)
Dzung L. Pham, Johns Hopkins Univ. (United States)
Jerry L. Prince, Johns Hopkins Univ. (United States)


Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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