000 | 04165cam a22005771i 4500 | ||
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001 | 9781351029261 | ||
003 | FlBoTFG | ||
005 | 20220711212852.0 | ||
006 | m d | ||
007 | cr ||||||||||| | ||
008 | 191029s2019 flua o 000 0 eng d | ||
040 |
_aOCoLC-P _beng _erda _epn _cOCoLC-P |
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020 |
_a9781351029247 _q(ePub ebook) : |
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020 | _a135102924X | ||
020 |
_a9781351029254 _q(PDF ebook) : |
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020 | _a1351029258 | ||
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_a9781351029230 _q(Mobipocket ebook) : |
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020 | _a1351029231 | ||
020 |
_a9781351029261 _q(ebook) : |
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020 | _a1351029266 | ||
020 | _z9780815361473 (hbk.) | ||
024 | 7 |
_a10.1201/9781351029261 _2doi |
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035 | _a(OCoLC)1127830069 | ||
035 | _a(OCoLC-P)1127830069 | ||
050 | 4 | _aQC762.6.M34 | |
072 | 7 |
_aMED _x009000 _2bisacsh |
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072 | 7 |
_aSCI _x055000 _2bisacsh |
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072 | 7 |
_aTEC _x015000 _2bisacsh |
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072 | 7 |
_aPHVN _2bicssc |
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082 | 0 | 4 |
_a538.36 _223 |
100 | 1 |
_aPaul, Joseph Suresh, _eauthor. _920330 |
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245 | 1 | 0 |
_aRegularized image reconstruction in parallel MRI with MATLAB / _cJoseph Suresh Paul, Raji Susan Mathew. |
250 | _a1st. | ||
264 | 1 |
_aBoca Raton : _bCRC Press, _c2019. |
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300 |
_a1 online resource : _billustrations (black and white) |
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336 |
_atext _2rdacontent |
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336 |
_astill image _2rdacontent |
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_acomputer _2rdamedia |
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_aonline resource _2rdacarrier |
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500 | _a<P>Preface. Acknowledgement. Author Biography. Parallel MR image reconstruction. Regularization techniques for MR image reconstruction. Regularization parameter selection methods in parallel MR image reconstruction. Multi-filter calibration for autocalibrating parallel MRI. Parameter adaptation for wavelet regularization in parallel MRI. Parameter adaptation for total variation based regularization in parallel MRI. Combination of parallel magnetic resonance imaging and compressed sensing using L1-SPIRiT. Matrix completion methods. References. L MATLAB Codes.</P> | ||
520 | _aRegularization becomes an integral part of the reconstruction process in accelerated parallel magnetic resonance imaging (pMRI) due to the need for utilizing the most discriminative information in the form of parsimonious models to generate high quality images with reduced noise and artifacts. Apart from providing a detailed overview and implementation details of various pMRI reconstruction methods, Regularized image reconstruction in parallel MRI with MATLAB examples interprets regularized image reconstruction in pMRI as a means to effectively control the balance between two specific types of error signals to either improve the accuracy in estimation of missing samples, or speed up the estimation process. The first type corresponds to the modeling error between acquired and their estimated values. The second type arises due to the perturbation of k-space values in autocalibration methods or sparse approximation in the compressed sensing based reconstruction model. Features: Provides details for optimizing regularization parameters in each type of reconstruction. Presents comparison of regularization approaches for each type of pMRI reconstruction. Includes discussion of case studies using clinically acquired data. MATLAB codes are provided for each reconstruction type. Contains method-wise description of adapting regularization to optimize speed and accuracy. This book serves as a reference material for researchers and students involved in development of pMRI reconstruction methods. Industry practitioners concerned with how to apply regularization in pMRI reconstruction will find this book most useful. | ||
588 | _aOCLC-licensed vendor bibliographic record. | ||
650 | 0 |
_aMagnetic resonance imaging. _94091 |
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650 | 7 |
_aMEDICAL / Biotechnology _2bisacsh _920331 |
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650 | 7 |
_aSCIENCE / Physics _2bisacsh _910678 |
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650 | 7 |
_aTECHNOLOGY / Imaging Systems _2bisacsh _910809 |
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700 | 1 |
_aMathew, Raji Susan, _eauthor. _920332 |
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856 | 4 | 0 |
_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9781351029261 |
856 | 4 | 2 |
_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf |
942 | _cEBK | ||
999 |
_c72358 _d72358 |