Fast automatic multi-atlas segmentation of the prostate from 3D MR images

J.A. Dowling, J. Fripp, S.S. Chandra, J.P.W. Pluim, J. Lambert, J. Parker, J. Denham, P.B. Greer, O. Salvado

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

44 Citations (Scopus)
5 Downloads (Pure)

Abstract

A fast fully automatic method of segmenting the prostate from 3D MR scans is presented, incorporating dynamic multi-atlas label fusion. The diffeomorphic demons method is used for non-rigid registration and a comparison of alternate metrics for atlas selection is presented. A comparison of results from an average shape atlas and the multi-atlas approach is provided. Using the same clinical dataset and manual contours from 50 clinical scans as Klein et al. (2008) a median Dice similarity coefficient of 0.86 was achieved with an average surface error of 2.00mm using the multi-atlas segmentation method. © 2011 Springer-Verlag.
Original languageEnglish
Title of host publicationProstate cancer imaging : image analysis and image-guided interventions : International Workshop, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 22, 2011. Proceedings
EditorsA. Madabhushi, J. Dowling, H. Huisman, D. Barratt
Place of PublicationBerlin
PublisherSpringer
Pages10-21
ISBN (Print)978-3-642-23943-4
DOIs
Publication statusPublished - 2011

Publication series

NameLecture Notes in Computer Science
Volume6963
ISSN (Print)0302-9743

Fingerprint

Dive into the research topics of 'Fast automatic multi-atlas segmentation of the prostate from 3D MR images'. Together they form a unique fingerprint.

Cite this