1st Edition

Stochastic Modeling for Medical Image Analysis

304 Pages 188 Color Illustrations

by CRC Press

304 Pages 188 Color Illustrations

by CRC Press

304 Pages

by CRC Press

Also available as eBook on:

Taylor & Francis eBooks
(Institutional Purchase)Opens in new tab or window

Description

Stochastic Modeling for Medical Image Analysis provides a brief introduction to medical imaging, stochastic modeling, and model-guided image analysis. Today, image-guided computer-assisted diagnostics (CAD) faces two basic challenging problems. The first is the computationally feasible and accurate modeling of images from different modalities to obtain clinically useful information. The second... Read more

Medical Imaging Modalities
Magnetic Resonance Imaging
Computed Tomography
Ultrasound Imaging
Nuclear Medical Imaging (Nuclide Imaging)
Bibliographic and Historical Notes

From Images to Graphical Models
Basics of Image Modeling
Pixel/Voxel Interactions and Neighborhoods
Exponential Families of Probability Distributions
Appearance and Shape Modeling
Bibliographic and Historical Notes

IRF Models: Estimating Marginals
Basic Independent Random Fields
Supervised and Unsupervised Learning
Expectation-Maximization to Identify Mixtures
Gaussian Linear Combinations versus Mixtures
Bibliographic and Historical Notes

Markov-Gibbs Random Field Models: Estimating Signal Interactions
Generic Kth-Order MGRFs
Common Second- and Higher-Order MGRFs
Learning Second-Order Interaction Structures
Bibliographic and Historical Notes

Applications: Image Alignment
General Image Alignment Frameworks
Global Alignment by Learning an Appearance Prior
Bibliographic and Historical Notes

Segmenting Multimodal Images
Joint MGRF of Images and Region Maps
Experimental Validation
Bibliographic and Historical Notes
Performance Evaluation and Validation

Segmenting with Deformable Models
Appearance-Based Segmentation
Shape and Appearance-Based Segmentation
Bibliographic and Historical Notes

Segmenting with Shape and Appearance Priors
Learning a Shape Prior
Evolving a Deformable Boundary
Experimental Validation
Bibliographic and Historical Notes

Cine Cardiac MRI Analysis
Segmenting Myocardial Borders
Wall Thickness Analysis
Experimental Results
Bibliographic and Historical Notes

Sizing Cardiac Pathologies
LV Wall Segmentation
Identifying the Pathological Tissue
Quantifying the Myocardial Viability
Performance Evaluation and Validation
Bibliographic and Historical Notes