Automatic detection of abnormal regions using guassian mixture model

Zhen Tian, Zouji Ying, Kehong Yuan

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Automatic detection of abnormal region, such as positions of lesions,disease locus, is an essential processing component for computer-aided medicalimage diagnosis. In this paper, we use gaussian mixture model (GMM,) to simulatethe process of doctors' checking medical images with their accumulated visualexperiences, which is based on the assumption that the normal region is thebackground and abnormal region is the foreground. We employ the brain CTsequences and index the similar slices in the anatomy axial direction. Thismethod was tested on brain CT image with different lesions and receivedfavorable results. ICIC International

Original languageEnglish (US)
Pages (from-to)921-926
Number of pages6
JournalICIC Express Letters
Volume3
Issue number4
StatePublished - Dec 2009

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Brain
Computer aided diagnosis
Processing

Keywords

  • Abnormal region detection
  • Gaussian mixture model
  • Medical images

ASJC Scopus subject areas

  • Computer Science(all)
  • Control and Systems Engineering

Cite this

Automatic detection of abnormal regions using guassian mixture model. / Tian, Zhen; Ying, Zouji; Yuan, Kehong.

In: ICIC Express Letters, Vol. 3, No. 4, 12.2009, p. 921-926.

Research output: Contribution to journalArticle

Tian, Z, Ying, Z & Yuan, K 2009, 'Automatic detection of abnormal regions using guassian mixture model', ICIC Express Letters, vol. 3, no. 4, pp. 921-926.
Tian, Zhen ; Ying, Zouji ; Yuan, Kehong. / Automatic detection of abnormal regions using guassian mixture model. In: ICIC Express Letters. 2009 ; Vol. 3, No. 4. pp. 921-926.
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