A state-of-the-art review of key topics in medical image perception science and practice, including associated techniques, illustrations and examples. This second edition contains extensive updates and substantial new content. Written by key figures in the field, it covers a wide range of topics including signal detection, image interpretation and advanced image analysis (e.g. deep learning) techniques for interpretive and computational perception. It provides an overview of the key techniques of medical image perception and observer performance research, and includes examples and applications across clinical disciplines including radiology, pathology and oncology. A final chapter discusses the future prospects of medical image perception and assesses upcoming challenges and possibilities, enabling readers to identify new areas for research. Written for both newcomers to the field and experienced researchers and clinicians, this book provides a comprehensive reference for those interested in medical image perception as means to advance knowledge and improve human health.

This state-of-the-art book reviews key issues and methods in medical image perception research through associated techniques, illustrations and examples. Written by key figures in the field, the book covers a range of topics including the history of medical image perception research, the basics of vision and cognition, and dedicated application areas, especially those concerned with the interface between the clinician and the display of medical image data. It summarizes many of the basic techniques used to conduct and analyze medical image perception and observer performance research, allowing readers to understand basic research techniques so they can adopt them for use in their own studies. Written for both newcomers to the field and experienced researchers, this book provides a broad overview of medical image perception, and will serve as a reference volume for years to come.