Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/40505
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dc.titleClassification of CT brain images of head trauma
dc.contributor.authorGong, T.
dc.contributor.authorLiu, R.
dc.contributor.authorTan, C.L.
dc.contributor.authorFarzad, N.
dc.contributor.authorLee, C.K.
dc.contributor.authorPang, B.C.
dc.contributor.authorTian, Q.
dc.contributor.authorTang, S.
dc.contributor.authorZhang, Z.
dc.date.accessioned2013-07-04T08:05:51Z
dc.date.available2013-07-04T08:05:51Z
dc.date.issued2007
dc.identifier.citationGong, T.,Liu, R.,Tan, C.L.,Farzad, N.,Lee, C.K.,Pang, B.C.,Tian, Q.,Tang, S.,Zhang, Z. (2007). Classification of CT brain images of head trauma. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4774 LNBI : 401-408. ScholarBank@NUS Repository.
dc.identifier.isbn9783540752851
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40505
dc.description.abstractA method for automatic classification of computed tomography (CT) brain images of different head trauma types is presented in this paper. The method has three major steps: 1. The images are first segmented to find potential hemorrhage regions using ellipse fitting, background removal and wavelet decomposition technique; 2. For each region, features (such as area, major axis length, etc.) are extracted; 3. Each extracted feature is classified using machine learning algorithm; the images are then classified based on its component regions' classification. The automatic medical image classification will be useful in building a content-based medical image retrieval system. © Springer-Verlag Berlin Heidelberg 2007.
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.volume4774 LNBI
dc.description.page401-408
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

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