ISBN: 9789811335969
Код товара 145696
Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms
ISBN: 9789811335969
Код товара 145696
16 769 ₽
Доставка под заказ
Если Вы закажете книгу до 15.04.2024, то мы привезём её ориентировочно 05.06.2024.
-
Автор
Bhabesh Deka; Sumit Datta
-
Издатель
Springer
-
Тип обложки
Hardcover
-
Размеры
239 x 218 x 10
-
Год издания
2019
-
Вес (г)
411
-
ISBN
9789811335969
-
Язык
ENG
-
Кол-во страниц
122
О чём книга?
This book presents a comprehensive review of the recent developments in fast L1-norm regularization-based compressed sensing (CS) magnetic resonance image reconstruction algorithms. Compressed sensing magnetic resonance imaging (CS-MRI) is able to reduce the scan time of MRI considerably as it is possible to reconstruct MR images from only a few measurements in the k-space; far below the requirements of the Nyquist sampling rate. L1-norm-based regularization problems can be solved efficiently using the state-of-the-art convex optimization techniques, which in general outperform the greedy techniques in terms of quality of reconstructions. Recently, fast convex optimization based reconstruction algorithms have been developed which are also able to achieve the benchmarks for the use of CS-MRI in clinical practice. This book enables graduate students, researchers, and medical practitioners working in the field of medical image processing, particularly in MRI to understand the need for the CS in MRI, and thereby how it could revolutionize the soft tissue imaging to benefit healthcare technology without making major changes in the existing scanner hardware. It would be particularly useful for researchers who have just entered into the exciting field of CS-MRI and would like to quickly go through the developments to date without diving into the detailed mathematical analysis. Finally, it also discusses recent trends and future research directions for implementation of CS-MRI in clinical practice, particularly in Bio- and Neuro-informatics 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.-
Подпишись на рассылку
Подпишись на рассылку
Знание — сила
Обещаем делиться новинками, статьями, подборками и всем, что действительно важно
P.S. спамить — не в нашем стиле
1.11 s.
|
s.