Compressed sensing for magnetic resonance image reconstruction:
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...
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| Main Author: | |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge
Cambridge University Press
2015
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| Subjects: | |
| Online Access: | BSB01 FHN01 UER01 Volltext |
| 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 |
| Item Description: | Title from publisher's bibliographic system (viewed on 06 Jun 2016) |
| Physical Description: | 1 online resource (xv, 206 pages) |
| ISBN: | 9781316217795 |
| DOI: | 10.1017/CBO9781316217795 |
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| contents | Mathematical techniques -- Single channel static MR image reconstruction -- Multi-coil parallel MRI reconstruction -- Dynamic MRI reconstruction -- Applications in other areas -- Some open problems |
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| discipline | Medizin |
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| id | DE-604.BV043940433 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:39:13Z |
| institution | BVB |
| isbn | 9781316217795 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029349403 |
| oclc_num | 967599903 |
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| physical | 1 online resource (xv, 206 pages) |
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| publishDate | 2015 |
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| publisher | Cambridge University Press |
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| spelling | Majumdar, Angshul Verfasser aut Compressed sensing for magnetic resonance image reconstruction Angshul Majumdar Cambridge Cambridge University Press 2015 1 online resource (xv, 206 pages) txt rdacontent c rdamedia cr rdacarrier 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 Compressed sensing (Telecommunication) Erscheint auch als Druck-Ausgabe 978-1-107-10376-4 https://doi.org/10.1017/CBO9781316217795 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Majumdar, Angshul Compressed sensing for magnetic resonance image reconstruction Mathematical techniques -- Single channel static MR image reconstruction -- Multi-coil parallel MRI reconstruction -- Dynamic MRI reconstruction -- Applications in other areas -- Some open problems Compressed sensing (Telecommunication) |
| title | Compressed sensing for magnetic resonance image reconstruction |
| title_auth | Compressed sensing for magnetic resonance image reconstruction |
| title_exact_search | Compressed sensing for magnetic resonance image reconstruction |
| title_full | Compressed sensing for magnetic resonance image reconstruction Angshul Majumdar |
| title_fullStr | Compressed sensing for magnetic resonance image reconstruction Angshul Majumdar |
| title_full_unstemmed | Compressed sensing for magnetic resonance image reconstruction Angshul Majumdar |
| title_short | Compressed sensing for magnetic resonance image reconstruction |
| title_sort | compressed sensing for magnetic resonance image reconstruction |
| topic | Compressed sensing (Telecommunication) |
| topic_facet | Compressed sensing (Telecommunication) |
| url | https://doi.org/10.1017/CBO9781316217795 |
| work_keys_str_mv | AT majumdarangshul compressedsensingformagneticresonanceimagereconstruction |