Description
This book provides an in-depth exploration of how artificial intelligence and machine learning are transforming medical image processing. It addresses both 2D and 3D imaging modalities, covering fundamental concepts through advanced applications in clinical practice.
Readers will discover cutting-edge algorithms for image segmentation, registration, reconstruction, and classification. The authors discuss deep learning architectures including convolutional neural networks, recurrent networks, and hybrid models specifically tailored for medical imaging applications.
The text includes practical case studies, implementation strategies, and best practices for developing AI-powered diagnostic systems. Topics span from image preprocessing and feature extraction to real-world deployment challenges. This resource is essential for researchers, practitioners, and students seeking to understand how machine learning enhances accuracy and efficiency in medical imaging workflows across various clinical domains.
Reviews
There are no reviews yet.