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

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