Semi-automatic Segmentation of the Prostate

Reyer Zwiggelaar, Yanong Zhu, Stuart Williams

Research output: Chapter in Book/Report/Conference proceedingChapter

39 Citations (Scopus)

Abstract

A semi-automatic method has been developed which segments the prostate in slices of Magnetic Resonance Imaging (MRI) data. The developed approach exploits the characteristics of the anatomical shape of the prostate when represented in a polar transform space. Simple techniques, such as line detection and non-maximum suppression, are used to track the boundary of the prostate. The initial results, based on a small set of data, indicate a good correlation with expert based manual segmentation.
Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Subtitle of host publicationFirst Iberian Conference, IbPRIA 2003 Puerto de Andratx, Mallorca, Spain, June 4–6, 2003 Proceedings
EditorsFrancisco Jose Perales, Aurelio J. C. Campilho, Nicolas Perez Perez, Nicolas Perez Perez
PublisherSpringer Nature
Pages1108-1116
Number of pages9
ISBN (Electronic)978-3-540-44871-6
ISBN (Print)3540402179, 9783540402176
DOIs
Publication statusPublished - 22 May 2003
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2652
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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