Mathematics and Computer Science in Medical Imaging

Mathematics and Computer Science in Medical Imaging

5.0 1
by Max A. Viergever

ISBN-10: 0387186727

ISBN-13: 9780387186726

Pub. Date: 01/01/1988

Publisher: Springer-Verlag New York, LLC

Product Details

Springer-Verlag New York, LLC
Publication date:
NATO Science Series

Table of Contents

1: Introduction to and Overview of the Field.- to integral transforms.- to discrete reconstruction methods in medical imaging.- Image structure.- Fundamentals of the Radon transform.- Regularization techniques in medical imaging.- Statistical methods in pattern recognition.- Image data compression techniques: A survey.- From 2D to 3D representation.- VLSI-intensive graphics systems.- Knowledge based interpretation of medical images.- 2: Selected Topics.- 2.1 Analytic Reconstruction Methods.- The attenuated Radon transform.- Inverse imaging with strong multiple scattering.- 2.2 Iterative Methods.- Possible criteria for choosing the number of iterations in some iterative reconstruction methods.- Initial performance of block-iterative reconstruction algorithms.- Maximum likelihood reconstruction in PET and TOFPET.- Maximum likelihood reconstruction for SPECT using Monte Carlo simulation.- X-ray coded source tomosynthesis.- Some mathematical aspects of electrical impedance tomography.- 2.3 Display and Evaluation.- Hierarchical figure-based shape description for medical imaging.- GIHS: A generalized color model and its use for the representation of multiparameter medical images.- The evaluation of image processing algorithms for use in medical imaging.- Focal lesions in medical images: A detection problem.- 2.4 Applications.- Time domain phase: A new tool in medical ultrasound imaging.- Performance of echographic equipment and potentials for tissue characterization.- Development of a model to predict the potential accuracy of vessel blood flow measurements from dynamic angiographic recordings.- The quantitative imaging potential of the HIDAC positron camera.- The use of cluster analysis and constrained optimisation techniques in factor analysis of dynamic structures.- Detection of elliptical contours.- Optimal non-linear filters for images with non-Gaussian differential distributions.- Participants.

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Mathematics and Computer Science in Medical Imaging 5 out of 5 based on 0 ratings. 1 reviews.
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