Regularized Image Reconstruction in Parallel MRI with MATLAB
Autor Joseph Suresh Paul, Raji Susan Mathewen Limba Engleză Hardback – 25 oct 2019
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.
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Specificații
ISBN-13: 9780815361473
ISBN-10: 0815361475
Pagini: 322
Ilustrații: 74
Dimensiuni: 178 x 254 x 25 mm
Greutate: 0.76 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
ISBN-10: 0815361475
Pagini: 322
Ilustrații: 74
Dimensiuni: 178 x 254 x 25 mm
Greutate: 0.76 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Cuprins
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.
Notă biografică
Joseph Suresh Paul
Joseph Suresh Paul is currently a Professor at the Indian Institute of Information Technology and Management- Kerala (IIITM-K), India. He obtained his Ph.D. degree in Electrical Engineering from the Indian Institute of Technology, Madras, India in the year 2000. His research is focused on MR imaging from the perspective of accelerating image acquisition, with the goal of enhancing clinically relevant features using filters integrated into the reconstruction process. His other interests include mathematical applications to problems in MR image reconstruction, compressed sensing, and super resolution techniques for MRI. He has published a number of articles in peer-reviewed international journals of high repute.
Raji Susan Mathew
Raji Susan Mathew is currently pursuing her Ph.D. degree in the area of MR image reconstruction. She received bachelor degree in Electronics and Communication Engineering from the Mahatma Gandhi university, Kottayam and master's degree in signal processing from the Cochin university of science and technology, Kochi in 2011 and 2013. She is a recipient of the Maulana Azad National Fellowship (MANF) by the University Grants Commission (UGC), India. Her research interests include regularization techniques for MR image reconstruction and Compressed Sensing.
Joseph Suresh Paul is currently a Professor at the Indian Institute of Information Technology and Management- Kerala (IIITM-K), India. He obtained his Ph.D. degree in Electrical Engineering from the Indian Institute of Technology, Madras, India in the year 2000. His research is focused on MR imaging from the perspective of accelerating image acquisition, with the goal of enhancing clinically relevant features using filters integrated into the reconstruction process. His other interests include mathematical applications to problems in MR image reconstruction, compressed sensing, and super resolution techniques for MRI. He has published a number of articles in peer-reviewed international journals of high repute.
Raji Susan Mathew
Raji Susan Mathew is currently pursuing her Ph.D. degree in the area of MR image reconstruction. She received bachelor degree in Electronics and Communication Engineering from the Mahatma Gandhi university, Kottayam and master's degree in signal processing from the Cochin university of science and technology, Kochi in 2011 and 2013. She is a recipient of the Maulana Azad National Fellowship (MANF) by the University Grants Commission (UGC), India. Her research interests include regularization techniques for MR image reconstruction and Compressed Sensing.
Descriere
This book provides a detailed discussion on the issues and challenges relating to choice and usage of regularization methods applied to pMRI reconstruction algorithms. The book summarizes aspects required for judiciously choosing regularization parameters for artifact and noise free reconstruction with relevance to specific reconstruction variant.