Automated detection of architectural distortion using improved adaptive Gabor filter

Ruriha Yoshikawa, Atsushi Teramoto, Tomoko Matsubara, Hiroshi Fujita

研究成果: Conference contribution

14 被引用数 (Scopus)

抄録

Architectural distortion in mammography is the most missing finding for radiologists, despite high malignancy. Many research groups have developed methods for automated detection of architectural distortion. However, improvement of their detection performance is desired. In this study, we developed a novel method for automated detection of architectural distortion in mammograms. To detect the mammary gland structure, we used an adaptive Gabor filter, whichconsists of three Gabor filters created by changing the combination of parameters. The filter that is best matched to the mammary gland structure pixel by pixel in the mammogram is selected. After detecting the mammary gland, enhancement of the concentrated region and false positive reduction are performed. In the experiments, we verified the detection performance of our method using 50 mammograms. The true positive rate was found to be 82.45%, and the number of false positive per image was 1.06. These results are similar to or better than those of existing methods. Therefore, the proposed method may be useful for detecting architectural distortion in mammograms.

本文言語English
ホスト出版物のタイトルBreast Imaging - 12th International Workshop, IWDM 2014, Proceedings
出版社Springer Verlag
ページ606-611
ページ数6
ISBN(印刷版)9783319078861
DOI
出版ステータスPublished - 01-01-2014
イベント12th International Workshop on Breast Imaging, IWDM 2014 - Gifu City, Japan
継続期間: 29-06-201402-07-2014

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
8539 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other12th International Workshop on Breast Imaging, IWDM 2014
国/地域Japan
CityGifu City
Period29-06-1402-07-14

All Science Journal Classification (ASJC) codes

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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