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Compressed sensing for magnetic resonance image reconstruction / Angshul Majumdar.

By: Majumdar, Angshul [author.].
Material type: materialTypeLabelBookPublisher: Cambridge : Cambridge University Press, 2015Description: 1 online resource (xv, 206 pages) : digital, PDF file(s).Content type: text Media type: computer Carrier type: online resourceISBN: 9781316217795 (ebook).Subject(s): Compressed sensing (Telecommunication)Additional physical formats: Print version: : No titleDDC classification: 616.07/548 Online resources: Click here to access online
Contents:
Mathematical techniques -- Single channel static MR image reconstruction -- Multi-coil parallel MRI reconstruction -- Dynamic MRI reconstruction -- Applications in other areas -- Some open problems.
Summary: Expecting the reader to have some basic training in liner algebra and optimization, the book begins with a general discussion on CS techniques and algorithms. It moves on to discussing single channel static MRI, the most common modality in clinical studies. It then takes up multi-channel MRI and the interesting challenges consequently thrown up in signal reconstruction. Off-line and on-line techniques in dynamic MRI reconstruction are visited. Towards the end the book broadens the subject by discussing how CS is being applied to other areas of biomedical signal processing like X-ray, CT and EEG acquisition. The emphasis throughout is on qualitative understanding of the subject rather than on quantitative aspects of mathematical forms. The book is intended for MRI engineers interested in the brass tacks of image formation; medical physicists interested in advanced techniques in image reconstruction; and mathematicians or signal processing engineers.
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Title from publisher's bibliographic system (viewed on 06 Jun 2016).

Mathematical techniques -- Single channel static MR image reconstruction -- Multi-coil parallel MRI reconstruction -- Dynamic MRI reconstruction -- Applications in other areas -- Some open problems.

Expecting the reader to have some basic training in liner algebra and optimization, the book begins with a general discussion on CS techniques and algorithms. It moves on to discussing single channel static MRI, the most common modality in clinical studies. It then takes up multi-channel MRI and the interesting challenges consequently thrown up in signal reconstruction. Off-line and on-line techniques in dynamic MRI reconstruction are visited. Towards the end the book broadens the subject by discussing how CS is being applied to other areas of biomedical signal processing like X-ray, CT and EEG acquisition. The emphasis throughout is on qualitative understanding of the subject rather than on quantitative aspects of mathematical forms. The book is intended for MRI engineers interested in the brass tacks of image formation; medical physicists interested in advanced techniques in image reconstruction; and mathematicians or signal processing engineers.

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