This edited book focuses on the application of AI and data analytics within the three specialisms of medical imaging: diagnostic radiography (including fluoroscopy, computed tomography, breast imaging, ultrasound, and magnetic resonance imaging), radiotherapy and oncology, and nuclear medicine and molecular imaging.

Artificial Intelligence and Data Analytics in Medical Imaging leverages the expertise of key practitioners, academics, and researchers who are recognized leaders in their respective fields. The chapters cover essential topics including imaging modalities, treatment planning, ethics, and future recommendations. The editors incorporate insights from recent publications and clinical practice, addressing how emerging technologies should be managed, implemented, and adapted in healthcare settings. Each chapter maintains a patient-centered focus while connecting to key literature in the field.

This book acts as a cornerstone for undergraduate students, but importantly 'signpost' to other key texts within the field of medical imaging. Further, academics will also find this text useful as it aims to enrich scholarly learning, teaching and assessment to healthcare programs nationally and internationally.