Observer Performance Methods for Diagnostic Imaging : Foundations, Modeling, and Applications with R-Based Examples book cover
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Observer Performance Methods for Diagnostic Imaging
Foundations, Modeling, and Applications with R-Based Examples





ISBN 9780367781637
Published March 31, 2021 by CRC Press
590 Pages

 
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Book Description

"This book presents the technology evaluation methodology from the point of view of radiological physics and contrasts the purely physical evaluation of image quality with the determination of diagnostic outcome through the study of observer performance. The reader is taken through the arguments with concrete examples illustrated by code in R, an open source statistical language."
–  from the Foreword by Prof. Harold L. Kundel, Department of Radiology, Perelman School of Medicine, University of Pennsylvania



"This book will benefit individuals interested in observer performance evaluations in diagnostic medical imaging and provide additional insights to those that have worked in the field for many years."
– Prof. Gary T. Barnes, Department of Radiology, University of Alabama at Birmingham





This book provides a complete introductory overview of this growing field and its applications in medical imaging, utilizing worked examples and exercises to demystify statistics for readers of any background. It includes a tutorial on the use of the open source, widely used R software, as well as basic statistical background, before addressing localization tasks common in medical imaging. The coverage includes a discussion of study design basics and the use of the techniques in imaging system optimization, memory effects in clinical interpretations, predictions of clinical task performance, alternatives to ROC analysis, and non-medical applications.



Dev P. Chakraborty, PhD, is a clinical diagnostic imaging physicist, certified by the American Board of Radiology in Diagnostic Radiological Physics and Medical Nuclear Physics. He has held faculty positions at the University of Alabama at Birmingham, University of Pennsylvania, and most recently at the University of Pittsburgh.



Table of Contents

1 Preliminaries





PART A The receiver operating characteristic (ROC) paradigm



2 The binary paradigm



3 Modeling the binary task



4 The ratings paradigm



5 Empirical AUC



6 Binormal model



7 Sources of variability in AUC





PART B Two significance testing methods for the ROC paradigm



8 Hypothesis testing



9 Dorfman–Berbaum–Metz–Hillis (DBMH) analysis



10 Obuchowski–Rockette–Hillis (ORH) analysis



11 Sample size estimation





PART C The free-response ROC (FROC) paradigm



12 The FROC paradigm



13 Empirical operating characteristics possible with FROC data



14 Computation and meanings of empirical FROC FOM-statistics and AUC measures



15 Visual search paradigms



16 The radiological search model (RSM)



17 Predictions of the RSM



18 Analyzing FROC data



19 Fitting RSM to FROC/ROC data and key findings





PART D Selected advanced topics



20 Proper ROC models



21 The bivariate binormal model



22 Evaluating standalone CAD versus radiologists



23 Validating CAD analysis

...
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Author(s)

Biography

Dev P. Chakraborty received his PhD in physics in 1977 from the University of Rochester, NY. Following postdoctoral fellowships at the University of Pennsylvania (UPENN) and the University of Alabama at Birmingham (UAB), since 1982 he has worked as a clinical diagnostic imaging physicist. He is American Board of Radiology certified in Diagnostic Radiological Physics and Medical Nuclear Physics (1987). He has held faculty positions at UAB (1982 - 1988), UPENN (1988-2002) and the University of Pittsburgh (2002-2016). At UPENN he supervised hospital imaging equipment quality control, resident physics instruction and conducted independent research. He is an author on 78 peer-reviewed publications, the majority of which are first-authored. He has received research funding from the Whittaker Foundation, the Office of Women's Health, the FDA, the DOD, and has served as principal investigator on several NIH RO1 grants.