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An interactive and adaptive joint source-channel coding for progressive transmission of medical images is proposed. A hierarchical alternative least squares (HALS) based compressive sensing (CS) is effectively used for adaptive selection of the wavelet coefficients and nonlinearly thresholding the transform coefficients. In this modality the source compression rate is influenced by the proximity to...
In tomographic image reconstruction from limited-view projections the underlying inverse problem is ill-posed with the rank-deficient system matrix. The minimal-norm least squares solution may considerably differs from the true solution, and hence a priori knowledge is needed to improve the reconstruction. In our approach, we assume that the true image presents sparse features with uniform spacial...
The 17 papers in this special issue present significant contributions in three primary areas: data acquisition and preprocessing; brain activity detection and pattern analysis; and brain functional connectivity. The papers selected in this special issue, provide an overview of the state-of-art in the exciting and fruitful field of signal processing and modeling of brain fMRI. We hope that this collection...
Approximate non-negative matrix factorization (NMF) is an emerging technique with a wide spectrum of potential applications in biomedical data analysis. In this paper, we proposed a new NMF algorithm with temporal smoothness constraint that aims to extract non-negative components that have meaningful physical or physiological interpretations. We propose two constraints and derive new multiplicative...
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