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Title: | Classification of CT brain images of head trauma | Authors: | Gong, T. Liu, R. Tan, C.L. Farzad, N. Lee, C.K. Pang, B.C. Tian, Q. Tang, S. Zhang, Z. |
Issue Date: | 2007 | Citation: | Gong, 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. | Abstract: | A 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. | Source Title: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | URI: | http://scholarbank.nus.edu.sg/handle/10635/40505 | ISBN: | 9783540752851 | ISSN: | 03029743 |
Appears in Collections: | Staff Publications |
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