High-Performance Medical Image Processing

High-Performance Medical Image Processing offers a deep dive into cutting-edge techniques for medical imaging professionals. Edited by Sanjay Saxena and Sudip Paul, this book navigates through key topics like parallel computing, multicore architectures, and machine learning applications in medical contexts. It's tailored for those seeking to enhance their understanding of both conventional and advanced MRI methods and the latest in hyperspectral image processing.

What You'll Learn

• Basic understanding of medical imaging modalities
• Application of parallel computing in imaging
• Techniques for 3D segmentation in tumor detection
• Use of machine learning for MRI image classification
• High-performance computing requirements in deep learning

Who This Book Is For

This book is for medical imaging professionals, researchers, and advanced students in biomedical engineering who are looking to expand their knowledge in high-performance computing applications within medical image processing.

What You Need to Know First

Readers should have a foundational understanding of medical imaging technologies and basic knowledge of computer science concepts, particularly in parallel computing and machine learning algorithms.

Why This Book

Unlike other texts, this book bridges the gap between theory and practical application by providing real-world case studies and examples, such as the detection of pulmonary nodules using statistical networks.

What's Inside

Edited by Sanjay Saxena and Sudip Paul, and published by Apple Academic Press Inc., this comprehensive 329-page volume includes detailed chapters on both foundational and advanced topics in medical imaging, supported by contributions from leading experts in the field.