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Showing 1 to 3 of 3 for “"Sparse Image Reconstruction"”.
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Dictionary learning for scalable sparse image representation
… one of the novel processing tools is signal sparse coding which represents signals as linear combinations of a few representational basis vectors i.e., atoms given an overcomplete dictionary. Applications that employ sparse representation are many such as denoising, compression, and …
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Bridging Mri Reconstruction Across Eras: From Novel Optimization Of Traditional Methods To Efficient Deep Learning Strategies
… the redundancy among these coils were used for image reconstruction. Following the clinical impact and success of PI methods, compressed sensing (CS) techniques were developed to reconstruct images by using compressibility of images in a pre-specified linear transform domain. Transform learning …
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Hardware acceleration for sparse Fourier image reconstruction
… important medical imaging algorithm: iterative sparse Fourier image reconstruction. We transform the algorithm to exploit massive parallelism available in the FPGA fabric. Our design allows different ways of chaining custom pipelined vector engines, so that different computations can be carried …