Prostate Segmentation Using Pixel Classification and Genetic Algorithms

A Point Distribution Model (PDM) of the prostate has been constructed and used to automatically outline the contour of the gland in transurethral ultrasound images. We developed a new, two stages, method: first the PDM is fitted, using a multi-population genetic algorithm, to a binary image produced...

Full description

Saved in:
Bibliographic Details
Published inLecture notes in computer science pp. 910 - 917
Main Author ARAMBULA COSIO, Fernando
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Artificial intelligence
Boundary segmentation
Computer science; control theory; systems
Exact sciences and technology
Genetic algorithms
Pattern recognition. Digital image processing. Computational geometry
Point distribution models
Image segmentation
Grey level image
Genetic algorithm
Classification
Binary image
Medical imagery
Prostate
Medical application
Pixel
Online AccessGet full text

Cover

More Information
Summary:A Point Distribution Model (PDM) of the prostate has been constructed and used to automatically outline the contour of the gland in transurethral ultrasound images. We developed a new, two stages, method: first the PDM is fitted, using a multi-population genetic algorithm, to a binary image produced from Bayesian pixel classification. This contour is then used during the second stage to seed the initial population of a simple genetic algorithm, which adjusts the PDM to the prostate boundary on a grey level image. The method is able to find good approximations of the prostate boundary in a robust manner. The method and its results on 4 prostate images are reported.
ISBN:9783540298960
3540298967
ISSN:0302-9743
1611-3349
DOI:10.1007/11579427_93