Volumetric segmentation via 3D active shape models

M. M. Dickens, S. S. Gleason, H. Sari-Sarraf

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

11 Scopus citations

Abstract

A volumetric image segmentation algorithm has been developed and implemented by extending a 2D algorithm based on active shape models. The new technique allows segmentation of 3D objects that are embedded within volumetric image data. The extension from 2D involved four components: landmarking, shape modeling, gray-level modeling, and segmentation. Algorithms and software tools have been implemented to allow a user to efficiently landmark a 3D object training set. Additional tools were built that subsequently,, generate models of 3D object shape and gray-level appearance based on this training data. An object segmentation strategy was implemented that optimizes these models to segment a previously unseen instance of the object. Results of this new 3D segmentation algorithm have been generated for a synthetic volumetric data set.

Original languageEnglish
Title of host publicationProceedings - 5th IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2002
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages248-252
Number of pages5
ISBN (Electronic)0769515371
DOIs
StatePublished - 2002
Event5th IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2002 - Santa Fe, United States
Duration: Apr 7 2002Apr 9 2002

Publication series

NameProceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation
Volume2002-January

Conference

Conference5th IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2002
Country/TerritoryUnited States
CitySanta Fe
Period04/7/0204/9/02

Keywords

  • Active shape model
  • Computed tomography
  • Data analysis
  • Deformable models
  • Electrical capacitance tomography
  • Image segmentation
  • Instruments
  • Laboratories
  • Magnetic resonance imaging
  • Statistics

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