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.

About the Authors

Ehsan Samei is Professor in Radiology, Physics, Biomedical Engineering, Electrical and Computer Engineering, and Medical Physics at Duke University, where he is the Chief of the Clinical Imaging Physics and the Director of the Medical Physics Graduate Program. His current research includes quality and dose metrics that are clinically relevant and that can be used to design and utilize advanced imaging technologies for optimum interpretive and quantitative performance.

Elizabeth Krupinski is a Professor and Vice Chair for Research at Emory University, Atlanta, in the Departments of Radiology, Psychology and Biomedical Informatics. Her research interests include medical image perception, assessment of observer performance, and human factors issues.

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