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Automatic prostate boundary recognition in sonographic images using feature model and genetic algorithm.
Author(s) -
Wu R Y,
Ling K V,
Ng W S
Publication year - 2000
Publication title -
journal of ultrasound in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 91
eISSN - 1550-9613
pISSN - 0278-4297
DOI - 10.7863/jum.2000.19.11.771
Subject(s) - robustness (evolution) , boundary (topology) , medicine , artificial intelligence , feature (linguistics) , pattern recognition (psychology) , genetic algorithm , algorithm , computer vision , computer science , mathematics , machine learning , mathematical analysis , biochemistry , chemistry , linguistics , philosophy , gene
This paper describes the development of a model‐based boundary recognition system for transrectal prostate ultrasonographic images. It consists of two techniques: boundary modeling and boundary searching with model constraints. To achieve higher specificity of the model, a method called feature modeling is derived from the existing point distribution modeling method. To improve the robustness of the searching technique, the genetic algorithm is used. Incremental genetic algorithm with crowding replacement and binary string chromosome type was found experimentally to give good search results. It was shown that the system could recognize the boundary with considerable accuracy and consistency within a few minutes in transrectal ultrasonographic images taken from approximate middle position of the prostate.