High-Performance Medical Image Processing

The processing of medical images in a reasonable timeframe and with high  definition is very challenging. This volume helps to meet that  challenge by presenting a thorough overview of medical imaging  modalities, its processing, high-performance computing, and the need to  embed parallelism in medical image processing techniques to achieve  efficient and fast results.

With contributions from researchers  from prestigious laboratories and educational institutions,  High-Performance Medical Image Processing provides important information  on medical image processing techniques, parallel computing techniques,  and embedding parallelism in different image processing techniques. A  comprehensive review of parallel algorithms in medical image processing  problems is a key feature of this book. The volume presents the relevant  theoretical frameworks and the latest empirical research findings in  the area and provides detailed descriptions about the diverse  high-performance techniques.

Topics discussed include parallel  computing, multicore architectures and their applications in image  processing, machine learning applications, conventional and advanced  magnetic resonance imaging methods, hyperspectral image processing,  algorithms for segmenting 2D slices for 3D viewing, and more. Case  studies, such as on the detection of cancer tumors, expound on the  information presented.

Key features:
Provides descriptions of  different medical imaging modalities and their applicationsDiscusses the  basics and advanced aspects of parallel computing with different  multicore architecturesExpounds on the need for embedding data and task  parallelism in different medical image processing techniquesPresents  helpful examples and case studies of the discussed methods
This book  will be valuable for professionals, researchers, and students working in  the field of healthcare engineering, medical imaging technology,  applications in machine and deep learning, and more. It is also  appropriate for courses in computer engineering, biomedical engineering  and electrical engineering based on artificial intelligence, parallel  computing, high performance computing, and machine learning and its  applications in medical imaging.