04104cam 22005651i 45000010014000000030008000140050017000220060019000390070015000580080041000730400035001140200034001490200015001830200033001980200015002310200040002460200015002860200029003010200015003300200025003450240031003700350022004010350024004230500016004470720025004630720025004880720025005130720017005380820015005551000034005702450107006042500009007112640036007203000057007563360021008133360028008343370023008623380032008855000573009175201635014905880047031256500032031726500037032046500031032416500042032727000033033148560072033478560102034199990017035219781351029261FlBoTFG20220531132428.0m d cr |||||||||||191029s2019 flua o 000 0 eng d aOCoLC-PbengerdaepncOCoLC-P a9781351029247q(ePub ebook) : a135102924X a9781351029254q(PDF ebook) : a1351029258 a9781351029230q(Mobipocket ebook) : a1351029231 a9781351029261q(ebook) : a1351029266 z9780815361473 (hbk.)7 a10.1201/97813510292612doi a(OCoLC)1127830069 a(OCoLC-P)1127830069 4aQC762.6.M34 7aMEDx0090002bisacsh 7aSCIx0550002bisacsh 7aTECx0150002bisacsh 7aPHVN2bicssc04a538.362231 aPaul, Joseph Suresh,eauthor.10aRegularized image reconstruction in parallel MRI with MATLAB /cJoseph Suresh Paul, Raji Susan Mathew. a1st. 1aBoca Raton :bCRC Press,c2019. a1 online resource :billustrations (black and white) atext2rdacontent astill image2rdacontent acomputer2rdamedia aonline resource2rdacarrier a
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.
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. aOCLC-licensed vendor bibliographic record. 0aMagnetic resonance imaging. 7aMEDICAL / Biotechnology2bisacsh 7aSCIENCE / Physics2bisacsh 7aTECHNOLOGY / Imaging Systems2bisacsh1 aMathew, Raji Susan,eauthor.403Taylor & Francisuhttps://www.taylorfrancis.com/books/9781351029261423OCLC metadata license agreementuhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf c72220d72220