Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms
Springer Verlag, Singapore
978-981-13-3596-9 (ISBN)
Dr. Bhabesh Deka has been an Associate Professor at the Department of Electronics and Communication Engineering (ECE) at Tezpur University, Assam, India since January 2012. He is also a Visvesvaraya Young Faculty Research Fellow (YFRF) of the Ministry of Electronics & Information Technology (MeitY), Government of India. His major research interests are image processing (particularly, inverse ill-posed problems), computer vision, compressive sensing MRI and biomedical signal analysis. He is actively engaged in the development of low-cost Internet of Things (IoT) enabled systems for mobile healthcare, high-throughput compressed sensing based techniques for rapid magnetic resonance image reconstruction, and parallel computing architectures for real-time image processing and computer vision applications. He has published a number of articles in peer-reviewed national and international journals of high repute. He is also a regular reviewer for a various leading journals, including IEEE Transactions on Image Processing, IEEE Access, IEEE Signal Processing Letters, IET Image Processing, IET Computer Vision, Biomedical Signal Processing and Control, Digital Signal Processing, and International Journal of Electronics and Communications (AEU). He is associated with a number of professional bodies and societies, like, Fellow, IETE; Senior Member, IEEE (USA); Member, IEEE Engineering in Medicine and Biology (EMB) Society (USA); and Life Member, Institution of Engineers (India). Mr. Sumit Datta is currently pursuing his Ph.D. in the area of compressed sensing magnetic resonance image reconstruction at the Department of Electronics and Communication Engineering (ECE), Tezpur University, Assam, India. He received his B.Tech. in Electronics and Communication Engineering from National Institute of Technology Agartala (NITA), Tripura, India, in 2011 and his M.Tech. in Bioelectronics from Tezpur University in 2014. His research interestsinclude image processing, biomedical signal and image processing, compressed sensing MRI, and parallel computing. He has published a number of articles in peer-reviewed national and international journals, such as IEEE Signal Processing Letters, IET Image Processing, Journal of Optics, and the Multimedia Tools and Applications.
1. Introduction to Compressed Sensing Magnetic Resonance Imaging.- 2. Compressed Sensing MRI Reconstruction Problem.- 3. Fast Algorithms for Compressed Sensing MRI Reconstruction.- 4. Simulation Results.- 5. Performance Evaluation and Benchmark Setting.- 6. Conclusions and Future Directions.
Erscheinungsdatum | 17.01.2019 |
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Reihe/Serie | Springer Series on Bio- and Neurosystems ; 9 |
Zusatzinfo | 23 Illustrations, color; 15 Illustrations, black and white; XIII, 122 p. 38 illus., 23 illus. in color. |
Verlagsort | Singapore |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Medizinische Fachgebiete ► Radiologie / Bildgebende Verfahren ► Kernspintomographie (MRT) |
Medizinische Fachgebiete ► Radiologie / Bildgebende Verfahren ► Radiologie | |
Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie | |
Technik ► Elektrotechnik / Energietechnik | |
Technik ► Medizintechnik | |
Schlagworte | Clinical CS-MRI • Composite splitting based CS-MRI • Compressed sensing MRI • CS-MRI reconstruction algorithm • Fast L1-norm regularization • k-space undersampling • Rapid magnetic resonance image reconstruction |
ISBN-10 | 981-13-3596-6 / 9811335966 |
ISBN-13 | 978-981-13-3596-9 / 9789811335969 |
Zustand | Neuware |
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