A curvelet-based morphological segmentation of abdominal CT images

M. Sakalli, T. D. Pham, Kin Man Lam, H. Yan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

This paper presents a segmentation methodology of abdominal axial CT images. The aim of the study is to determine the location of mesenteric area from the axial images so the organs enclosed within can be localized precisely for diagnostic purposes. The challenge confronted here is that there is no a certain deterministic shape of abdominal organs. The methodology implemented here utilizes a curvelets stage followed by morphological image processing to achieve a contour emphasized segmentation from the gestalts of surrounding organs. This paper gives a detailed analysis of approach taken with the problems faced and a brief comparison wrt to other wavelet approaches.
Original languageEnglish
Title of host publication2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
PublisherIEEE
Pages5542-5545
Number of pages4
ISBN (Electronic)9781424479290
DOIs
Publication statusPublished - 1 Jan 2014
Event2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States
Duration: 26 Aug 201430 Aug 2014

Conference

Conference2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Country/TerritoryUnited States
CityChicago
Period26/08/1430/08/14

Keywords

  • abdominal image segmentation
  • connected-components labeling
  • curvelets
  • edge and contour detection
  • non-maximal suppression
  • wavelets

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications
  • Biomedical Engineering
  • Medicine(all)

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