Publication:
A curvelet-based morphological segmentation of abdominal CT images

dc.contributor.authorsSakalli M., Pham T.D., Lam K.M., Yan H.
dc.date.accessioned2022-03-15T02:10:16Z
dc.date.accessioned2026-01-10T19:51:28Z
dc.date.available2022-03-15T02:10:16Z
dc.date.issued2014
dc.description.abstractThis 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. © 2014 IEEE.
dc.identifier.doi10.1109/EMBC.2014.6944882
dc.identifier.isbn9781424479290
dc.identifier.pubmed25571250
dc.identifier.urihttps://hdl.handle.net/11424/247457
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectabdominal image segmentation
dc.subjectconnected-components labeling
dc.subjectcurvelets
dc.subjectedge and contour detection
dc.subjectnon-maximal suppression
dc.subjectnon-maximal suppression
dc.subjectwavelets
dc.titleA curvelet-based morphological segmentation of abdominal CT images
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.endPage5545
oaire.citation.startPage5542
oaire.citation.title2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Files