Main description:

Substantial developments in radiology/imaging methods have been achieved in recent years for disease diagnosis, prognostic classification, monitoring and evaluation of treatment efficacy, as well as the technological advances that result in better and efficient imaging processing. Statistics has played an important role in the evaluation and validation of these techniques and their clinical utilities. While there are books targeting statisticians to use the new tools developed exclusively for this biotechnological revolution, there are, however, few books targeting non-statistical radiological researchers who should be the advocators and users of the statistical tools. This book thus focuses on application instead of the detailed derivation of statistical theory. The practical approach will help radiologists and researchers understand the statistical methods used in their literature, and comprehend which methods they can order (from their local statistical restaurants with professional statistician chiefs) for their particular studies.

Contents:

Introduction of Statistical Thinking; Generalized Linear Models; Statistical Methods for Small Samples; Statistical Concepts for Disease Screening; Statistical Issues in Designing Screening Trials Using Imaging Methods; Statistical Concepts for Medical Diagnosis; Discriminant Analysis: Recursive Partitioning and Classifications; ROC Analysis and AFROC; Statistical Concepts for Patient Monitoring; Longitudinal Data and Measurement of Changes; Survival Analysis; Clinical Trials Using Imaging Endpoints; Statistical Concepts for Validation of an Imaging Technique; Clinical Trials for Evaluating and Validation Imaging Tools; Meta-Analysis of Imaging Studies; Cost-Effectiveness of Diagnostic Methods; Statistical Methods for Imaging Processing; Bayesian Statistics and Imaging Reconstruction; Markov Chain Monte Carlo Simulation in Imaging; Bootstrap Methods and Their Applications in Diffusion Tensor Imaging; Statistical Methods for Imaging Comparisons.