Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging provides a comprehensive examination of how machine learning and deep learning technologies are transforming diagnostic radiology and medical image analysis. This groundbreaking text bridges the gap between computer science and clinical medicine, making complex AI concepts accessible to healthcare professionals.

The book covers fundamental machine learning principles, convolutional neural networks, and their applications across all imaging modalities including radiography, CT, MRI, ultrasound, and nuclear medicine. Each chapter presents real-world clinical applications with validated algorithms and discusses implementation challenges in healthcare settings.

Special sections address regulatory considerations, FDA approval pathways, algorithm validation methodologies, and ethical implications of AI-assisted diagnosis. The text also explores emerging applications in radiomics, image reconstruction, and workflow optimization.

Written by an interdisciplinary team of radiologists, computer scientists, and AI researchers, this volume provides both theoretical foundations and practical guidance for integrating AI tools into clinical practice while maintaining diagnostic accuracy and patient safety.