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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.
Detection Theory is an introduction to one of the most important tools for analysis of data where choices must be made and performance is not perfect. Originally developed for evaluation of electronic detection, detection theory was adopted by psychologists as a way to understand sensory decision making, then embraced by students of human memory. It has since been utilized in areas as diverse as animal behavior and X-ray diagnosis. This book covers the basic principles of detection theory, with separate initial chapters on measuring detection and evaluating decision criteria. Some other features include: *complete tools for application, including flowcharts, tables, pointers, and software; *student-friendly language; *complete coverage of content area, including both one-dimensional and multidimensional models; *separate, systematic coverage of sensitivity and response bias measurement; *integrated treatment of threshold and nonparametric approaches; *an organized, tutorial level introduction to multidimensional detection theory; *popular discrimination paradigms presented as applications of multidimensional detection theory; and *a new chapter on ideal observers and an updated chapter on adaptive threshold measurement. This up-to-date summary of signal detection theory is both a self-contained reference work for users and a readable text for graduate students and other researchers learning the material either in courses or on their own.
This book is being reprinted to fill in the gap in literature on Signal Detection Theory, a theory that is still important in psychology, hearing, vision, audiology, and related subjects. There are a few books at the introductory level for undergraduates
Handbook of Perception, Volume II: Psychophysical Judgment and Measurement brings together a very large, diverse, and widely scattered literature on human perception, with emphasis on psychophysical judgement and measurement. The book reviews the history of research on choice, judgement, and measurement in order to provide a background for contemporary work. This volume is organized into five sections encompassing 14 chapters and begins with a historical background on psychophysics and the evolution of thinking about the central measurement problem in judgement. The basic psychological context in which choice and judgement occur is considered next, touching on topics such as the problem of information selection and the sources of bias and variability in judgemental processes in relation to memory. The chapters that follow discuss the theoretical frame of measurement models and their applications. In particular, examples of algebraic fundamental measurement, algebraic derived measurement, and probabilistic derived measurement are given. The book also introduces the reader to various psychophysical scaling methods and theories of scaling. This book will serve as a basic source and reference work for psychologists and natural scientists, as well as for anyone in the arts or sciences or those who are interested in human perception.
The book summarizes the application of signal detection theory to the analysis an measurement of humn observer's sensor sysem. The theory provides a way to analyze what had been called the threshold or sensory limen, the basic unit of all discrimination studies, whether human or animal. The book outlines the theory of statisical decision making and its application to a variety of common psychophysical processes. It shows how signal detection theory can be used to separate sensory and decision aspects of responses in dicrimination. The concepts of the ideal observer and energy detector are presented and compared with human auditory detection data. Signal detection theory is appliced to a variety of other substanditive problemsin sensory psychology. Signal Detection Theory and Psychology is an invaluable book for psychologists dealing with sensory perception, especailly auditory, for psychologists studying discrimination in other cognitivie processes, and for human factor engineers dealing with man/machine interfaces.
Detection theory has been applied to a host of varied problems (for example, measuring the accuracy of diagnostic systems or reliability of lie detection tests) and extends far beyond the detection of signals. This book is a primer on the subject.
Detection Theory: A User’s Guide is an introduction to one of the most important tools for the analysis of data where choices must be made and performance is not perfect. In these cases, detection theory can transform judgments about subjective experiences, such as perceptions and memories, into quantitative data ready for analysis and modeling. For beginners, the first three chapters introduce measuring detection and discrimination, evaluating decision criteria, and the utility of receiver operating characteristics. Later chapters cover more advanced research paradigms, including: complete tools for application, including flowcharts, tables, and software; student-friendly language; complete coverage of content area, including both one-dimensional and multidimensional models; integrated treatment of threshold and nonparametric approaches; an organized, tutorial level introduction to multidimensional detection theory; and popular discrimination paradigms presented as applications of multidimensional detection theory. This modern summary of signal detection theory is both a self-contained reference work for users and a readable text for graduate students and researchers learning the material either in courses or on their own.
This book is an international collection of contributions from academia, industry and the armed forces. It addresses current and emerging Spatial Vision Models and their application to the understanding, prediction and evaluation of the tasks of target detection and recognition. The discussion in many of the chapters is framed in terms of military targets and military vision aids. However, the techniques analyses and problems are by no means limited to this area of application. The detection and recognition of an armored vehicle from a reconnaissance image are performed by the same visual system used to detect and recognize a tumor in an X-ray. The analysis of the interaction of the human visual system with night vision devices is not different from the analysis needed in the case of an operator examining structures using a remote (endoscopic) camera, etc. The book is organized into three general sections. The first covers basic modeling of central (foveal) vision and its theoretical background. The second is centered on the evaluation of model performance in applications, while the third is dedicated to aspects of peripheral vision modeling and the expansion of peripheral modeling to include visual search.