Computational methods for image reconstruction

Reconstructing images from indirect measurements is a central problem in many applications, including the subject of this special issue, quantitative susceptibility mapping (QSM). The process of image reconstruction typically requires solving an inverse problem that is ill‐posed and large‐scale and...

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Bibliographic Details
Published in:	NMR in biomedicine Vol. 30; no. 4; pp. np - n/a
Main Authors:	Chung, Julianne, Ruthotto, Lars
Format:	Journal Article
Language:	English
Published:	England Wiley Subscription Services, Inc 01.04.2017
Subjects:	Algorithms Animals Brain - anatomy & histology Brain - physiology Brain Mapping - methods deconvolution Diffusion Magnetic Resonance Imaging - methods Humans ill‐posed Image Enhancement - methods Image Interpretation, Computer-Assisted - methods iterative methods linear inverse problems Models, Biological quantitative susceptibility mapping (QSM) regularization Reproducibility of Results Sensitivity and Specificity Tikhonov total variation deconvolution iterative methods linear inverse problems quantitative susceptibility mapping (QSM) ill-posed regularization total variation Tikhonov
ISSN:	0952-3480, 1099-1492, 1099-1492
Online Access:	Get full text
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