High Performance Medical Image Processing (Original PDF From Publisher)

High Performance Medical Image Processing (Original PDF From Publisher)

Written by Sanjay Saxena

It is quite difficult to process medical photos in a fair amount of time and with good resolution.

By providing a comprehensive review of medical imaging modalities, processing, high-performance computing, and the necessity of

integrating parallelism into medical image processing approaches to produce effective and quick results, this volume contributes to

meeting that challenge.

High-Performance Medical Image Processing offers valuable insights into medical image processing methods, parallel computing

strategies and integrating parallelism into various image processing techniques, thanks to the contributions of researchers from

esteemed laboratories and academic institutions.

One important aspect of this book is a thorough discussion of parallel techniques in medical image processing applications.

The text offers thorough explanations of the various high-performance strategies along with the most recent empirical research

findings and pertinent theoretical frameworks.

Parallel computing, hyperspectral image processing, traditional and sophisticated magnetic resonance imaging techniques, machine

learning applications, multicore architectures and their applications in image processing, algorithms for segmenting 2D slices for 3D

viewing and other topics are covered.

Case studies provide further information on the topics covered, such as the identification of cancerous tumors.

Important characteristics:

explains the many medical imaging modalities and how they are used.

covers both the fundamentals and cutting edge of parallel computing using various multicore architectures.

explains the necessity of job parallelism and data embedding in various medical image processing methods.gives practical illustrations

and case studies of the techniques covered.

Professionals, researchers and students working in the fields of medical imaging technologies, machine and deep learning applications

, healthcare engineering and more will find this book to be beneficial.

Courses in computer engineering, biomedical engineering and electrical engineering that focus on machine learning, artificial

intelligence , parallel computing, high speed computing, and its applications in medical imaging are also suitable for this material.