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Medical image processing is a complex task that requires efficient and fast results. The processing of medical images in a reasonable timeframe and with high definition is a significant challenge in the field of healthcare engineering. To meet this challenge, it’s essential to have a thorough understanding of medical imaging modalities, high-performance computing, and the need to embed parallelism in medical image processing techniques.
High-Performance Medical Image Processing provides a comprehensive overview of medical imaging modalities, parallel computing techniques, and the importance of embedding parallelism in different image processing techniques. Contributions from renowned researchers from prestigious laboratories and educational institutions offer valuable insights into medical image processing techniques, parallel computing, and high-performance computing.
A key feature of this book is the comprehensive review of parallel algorithms in medical image processing problems. Theoretical frameworks and empirical research findings are presented to provide a detailed understanding of high-performance techniques. Topics discussed include:
The book presents case studies on the detection of cancer tumors, showcasing the practical applications of medical image processing techniques. These examples provide valuable insights into the implementation of high-performance medical image processing techniques in real-world scenarios.
High-Performance Medical Image Processing is an essential resource for professionals, researchers, and students working in the field of healthcare engineering, medical imaging technology, machine learning, and parallel computing. It’s also an excellent textbook for courses in computer engineering, biomedical engineering, electrical engineering, and artificial intelligence.
Key features of this book include:
Publisher: Apple Academic Press
Publication Date: July 7, 2022
Language: English
ISBN: 9781774637227, 9781000410358
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