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Classification of CT Brain Images of Head Trauma

  • Tianxia Gong
  • Ruizhe Liu
  • Chew Lim Tan
  • Neda Farzad
  • Cheng Kiang Lee
  • Boon Chuan Pang
  • Qi Tian
  • Suisheng Tang
  • Zhuo Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4774)

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.

Keywords

Gray Matter Head Trauma Background Removal Ellipse Fitting Hemorrhage Region 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Tianxia Gong
    • 1
  • Ruizhe Liu
    • 1
  • Chew Lim Tan
    • 1
  • Neda Farzad
    • 2
  • Cheng Kiang Lee
    • 3
  • Boon Chuan Pang
    • 3
  • Qi Tian
    • 4
  • Suisheng Tang
    • 4
  • Zhuo Zhang
    • 4
  1. 1.Department of Computer Science, School of Computing, National University of Singapore, 3 Science Drive 2, 117543Singapore
  2. 2.Department of Learning, Management, Informatics & Ethics (LIME), Karolinska Institute Berzelius v. 3, Stockholm, 17177Sweden
  3. 3.National Neuroscience Institute, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, 308433Singapore
  4. 4.Insitute of Infocomm Research, 21 Heng Mui Keng Terrace, 119613Singapore

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