By a News Reporter-Staff News Editor at Journal of Technology -- Investigators publish new report on Sensor Research. According to news reporting out of Delhi, India, by VerticalNews editors, research stated, "This work addresses the problem of recovering multi-echo T1 or T2 weighted images from their partial K-space scans. Recent studies have shown that the best results are obtained when all the multi-echo images are reconstructed by simultaneously exploiting their intra-image spatial redundancy and inter-echo correlation."
Our news journalists obtained a quote from the research from the Institute of Information Technology, "The aforesaid studies either stack the vectorised images (formed by row or columns concatenation) as columns of a Multiple Measurement Vector (MMV) matrix or concatenate them as a long vector. Owing to the inter-image correlation, the thus formed MMV matrix or the long concatenated vector is row-sparse or group-sparse respectively in a transform domain (wavelets). Consequently the reconstruction problem was formulated as a row-sparse MMV recovery or a group-sparse vector recovery. In this work we show that when the multi-echo images are arranged in the MMV form, the thus formed matrix is low-rank. We show that better reconstruction accuracy can be obtained when the information about rank-deficiency is incorporated into the row/group sparse recovery problem. Mathematically, this leads to a constrained optimization problem where the objective function promotes the signal's groups-sparsity as well as its rank-deficiency; the objective function is minimized subject to data fidelity constraints. The experiments were carried out on ex vivo and in vivo T2 weighted images of a rat's spinal cord."
According to the news editors, the research concluded: "Results show that this method yields considerably superior results than state-of-the-art reconstruction techniques."
For more information on this research see: Rank awareness in group-sparse recovery of multi-echo MR images. Sensors, 2013;13(3):3902-21. (Elsevier - www.elsevier.com; Sensors - www.elsevier.com/wps/product/cws_home/504103)
Our news journalists report that additional information may be obtained by contacting A. Majumdar, Indraprastha Institute of Information Technology, Delhi 110020, India.
Keywords for this news article include: Asia, Delhi, India, Sensor Research.
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