Applications of Artificial Intelligence in Medical Imaging 1st Edition

Applications of Artificial Intelligence in Medical Imaging — 1st Edition by Abdulhamit Subasi is an authoritative, practical guide that bridges cutting-edge AI techniques and real-world diagnostic imaging. Captivating and clear, this book draws immediate attention with its focus on transforming radiology, pathology, and clinical workflows through intelligent image analysis.

Dive into expertly explained methods — from classical machine learning to deep learning architectures — applied across CT, MRI, PET, ultrasound, and digital pathology. Rich with algorithmic insights, evaluation metrics, and illustrative case examples, it explains segmentation, classification, detection, and image enhancement in a way both researchers and busy clinicians can apply. Emphasis on reproducible approaches, dataset considerations, and performance interpretation makes complex topics accessible without sacrificing rigor.

Imagine accelerating diagnosis, improving lesion detection, and reducing false positives across hospital departments and research labs. This volume appeals to radiologists, biomedical engineers, data scientists, medical students, and health system leaders seeking practical AI adoption strategies. It also addresses ethical, validation, and deployment challenges essential for safe translation into clinical practice.

Ideal for professionals and institutions in the US, Europe, Asia-Pacific, and beyond, the book is a go-to resource for anyone implementing AI-driven imaging solutions in diverse healthcare settings. Clear, targeted, and solution-oriented, it delivers both foundational knowledge and actionable techniques.

Order your copy today to equip your team with the tools to advance diagnostic accuracy and operational efficiency — a must-have reference for the future of medical imaging and AI in healthcare.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.