Buch, Englisch, 590 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 1098 g
Foundations, Modeling, and Applications with R-Based Examples
Buch, Englisch, 590 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 1098 g
Reihe: Imaging in Medical Diagnosis and Therapy
ISBN: 978-0-367-78163-7
Verlag: CRC Press
– 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.
Zielgruppe
Academic and Professional Practice & Development
Autoren/Hrsg.
Fachgebiete
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Bildgebende Verfahren, Nuklearmedizin, Strahlentherapie Radiologie, Bildgebende Verfahren
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
- Naturwissenschaften Physik Physik Allgemein
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Bildgebende Verfahren, Nuklearmedizin, Strahlentherapie Nuklearmedizin, PET, Radiotherapie
Weitere Infos & Material
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