Statistics of Medical Imaging
Chapman & Hall/CRC Interdisciplinary Statistics Series

Statistical investigation into technology not only provides a better understanding of the intrinsic features of the technology (analysis), but also leads to an improved design of the technology (synthesis). Physical principles and mathematical procedures of medical imaging technologies have been extensively studied during past decades. However, less work has been done on the statistical aspects of these techniques. Statistics of Medical Imaging fills this gap and provides a theoretical framework for statistical investigation into medical imaging technologies.

Features

• Describes physical principles and mathematical procedures of two medical imaging techniques: X-ray CT and MRI
• Presents statistical properties of imaging data (measurements) at each stage in the imaging processes of X-ray CT and MRI
• Demonstrates image reconstruction as a transform from a set of random variables (imaging data) to another set of random variables (image data)
• Presents statistical properties of image data (pixel intensities) at three levels: a single pixel, any two pixels, and a group of pixels (a region)
• Provides two stochastic models for X-ray CT and MR image in terms of their statistics and two model-based statistical image analysis methods
• Evaluates statistical image analysis methods in terms of their detection, estimation, and classification performances
• Indicates that X-ray CT, MRI, PET and SPECT belong to a category of imaging: the non-diffraction computed tomography

Rather than offering detailed descriptions of statistics of basic imaging protocols of X-ray CT and MRI, this book provides a method to conduct similar statistical investigations into more complicated imaging protocols.

Introduction. X-Ray CT Physics and Mathematics. MRI Physics and Mathematics. Non-Diffraction Computed Tomography. Statistics of X-Ray CT Imaging. Statistics of X-Ray CT Image. Statistics of MR Imaging. Statistics of MR Image. Stochastic Image Models. Statistical Image Analysis – I. Statistical Image Analysis – II. Performance Evaluation of Image Analysis Methods.

Tianhu Lei is an associate professor at the University of Pittsburgh. He has previously worked at the University of Maryland, the University of Pennsylvania, and the Children’s Hospital of Philadelphia. He earned a Ph.D. in electric and system engineering from the University of Pennsylvania.