Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/40412
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dc.titleAutomatic extraction of femur contours from hip x-ray images
dc.contributor.authorChen, Y.
dc.contributor.authorEe, X.
dc.contributor.authorLeow, W.K.
dc.contributor.authorHowe, T.S.
dc.date.accessioned2013-07-04T08:03:42Z
dc.date.available2013-07-04T08:03:42Z
dc.date.issued2005
dc.identifier.citationChen, Y.,Ee, X.,Leow, W.K.,Howe, T.S. (2005). Automatic extraction of femur contours from hip x-ray images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3765 LNCS : 200-209. ScholarBank@NUS Repository.
dc.identifier.isbn3540294112
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40412
dc.description.abstractExtraction of bone contours from x-ray images is an important first step in computer analysis of medical images. It is more complex than the segmentation of CT and MR images because the regions delineated by bone contours are highly nonuniform in intensity and texture. Classical segmentation algorithms based on homogeneity criteria are not applicable. This paper presents a model-based approach for automatically extracting femur contours from hip x-ray images. The method works by first detecting prominent features, followed by registration of the model to the x-ray image according to these features. Then the model is refined using active contour algorithm to get the accurate result. Experiments show that this method can extract the contours of femurs with regular shapes, despite variations in size, shape and orientation. © Springer-Verlag Berlin Heidelberg 2005.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume3765 LNCS
dc.description.page200-209
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

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