Mathematics and Computer Science in Medical Imaging by Max A. Viergever | 9783540186724 | Hardcover | Barnes & Noble
Mathematics and Computer Science in Medical Imaging

Mathematics and Computer Science in Medical Imaging

5.0 1
by Max A. Viergever

ISBN-10: 3540186727

ISBN-13: 9783540186724

Pub. Date: 01/28/1988

Publisher: Springer Berlin Heidelberg

Product Details

Springer Berlin Heidelberg
Publication date:
Nato ASI Subseries F:, #39
Product dimensions:
6.69(w) x 9.53(h) x (d)

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.

Customer Reviews

Average Review:

Write a Review

and post it to your social network


Most Helpful Customer Reviews

See all customer reviews >

Mathematics and Computer Science in Medical Imaging 5 out of 5 based on 0 ratings. 1 reviews.
pinpointAR More than 1 year ago
I’m loving McDonalds for fast food... MyDeals247 for the best deals;))