Computer-aided detection of multiple sclerosis lesions in brain magnetic resonance images: False positive reduction scheme consisted of rule-based, level set method, and support vector machine

Daisuke Yamamoto, Hidetaka Arimura, Shingo Kakeda, Taiki Magome, Yasuo Yamashita, Fukai Toyofuku, Masafumi Ohki, Yoshiharu Higashida, Yukunori Korogi

研究成果: Contribution to journalArticle査読

50 被引用数 (Scopus)

抄録

The purpose of this study was to develop a computerized method for detection of multiple sclerosis (MS) lesions in brain magnetic resonance (MR) images. We have proposed a new false positive reduction scheme, which consisted of a rule-based method, a level set method, and a support vector machine. We applied the proposed method to 49 slices selected from 6 studies of three MS cases including 168 MS lesions. As a result, the sensitivity for detection of MS lesions was 81.5% with 2.9 false positives per slice based on a leave-one-candidate-out test, and the similarity index between MS regions determined by the proposed method and neuroradiologists was 0.768 on average. These results indicate the proposed method would be useful for assisting neuroradiologists in assessing the MS in clinical practice.

本文言語英語
ページ(範囲)404-413
ページ数10
ジャーナルComputerized Medical Imaging and Graphics
34
5
DOI
出版ステータス出版済み - 7 2010

All Science Journal Classification (ASJC) codes

  • 放射線技術および超音波技術
  • 放射線学、核医学およびイメージング
  • コンピュータ ビジョンおよびパターン認識
  • 健康情報学
  • コンピュータ グラフィックスおよびコンピュータ支援設計

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