2019
DOI: 10.1142/s0219691319500036
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On curvelet CS reconstructed MR images and GA-based fuzzy conditional entropy maximization for segmentation

Abstract: In many practical situations, magnetic resonance imaging (MRI) needs reconstruction of images at low measurements, far below the Nyquist rate, as sensing process may be very costly and slow enough so that one can measure the coefficients only a few times. Segmentation of such subsampled reconstructed MR images for medical analysis and diagnosis becomes a challenging task due to the inherent complex characteristics of the MR images. This paper considers reconstruction of MR images at compressive sampling (or co… Show more

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References 37 publications
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