Automatic segmentation of the prostate in 3D magnetic resonance images using case specific deformable models

Sh. Chandra, J. Dowling, K. Shen, J.P.W. Pluim, P. Greer, O. Salvado, J. Fripp

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

5 Citations (Scopus)

Abstract

This paper presents a novel approach to automatically segment the prostate (including seminal vesicles) using a surface that is actively deformed via shape and gray level models. The surface deformation process utilises the results of a multi-atlas registration approach, where training images are matched to the case image via non-rigid registration. Normalised mutual information is then used to measure the similarity between each image in the training set and the case image. The set of training images with a similarity greater than a threshold is then used to build the initialisation and the gray level model of the segmentation process. This case specific gray level model is used to deform the initial surface to more closely match the prostate boundary via normalised cross-correlation based template matching of gray level profiles. Mean and median Dice's Similarity Coefficients of 0.849 and 0.855, as well as a mean surface error of 2.11 mm, were achieved when segmenting 3T Magnetic Resonance clinical scans of fifty patients.

Original languageEnglish
Title of host publicationProceedings - 2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011, 6-8 December 2011, Noosa, Queensland
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages7-12
Number of pages6
ISBN (Print)978-1-4577-2006-2
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011 - Noosa, QLD, Australia
Duration: 6 Dec 20118 Dec 2011

Conference

Conference2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011
Country/TerritoryAustralia
CityNoosa, QLD
Period6/12/118/12/11

Keywords

  • Multi-Atlas
  • Prostate
  • Segmentation
  • Shape Models

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