Patch clustering is involved into a number of inverse problems in MRI processing, such as image denoising, cross modality synthesis, parallel imaging reconstruction, super-resolution, under-sampled reconstruction, image registration and even segmentation. Considering that the MR signals are acquired in the k-space and then are Fourier transformed into the spatial domain, in this work we propose a new clustering method based on the features extracted from the frequency spectrum, which can be either applied alone for patch or image clustering, or combined with feature descriptors in the spatial domain to facilitate inverse problems processing in MRI.
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