Presentation 2002/11/1
An automated detection of architectural distortions on mammograms
Tomoko Matsubara, Tetsuko Ichikawa, Takeshi Hara, Hiroshi Fujita, Satoshi Kasai, Tokiko Endo, Takuji Iwase,
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Abstract(in English) The architectural distortion is a very important finding in interpreting breast cancers as well as microcalcification and mass on mammograms. In despite of the importance for detecting architectural distortions, no algorithms for detecting them have been reported. The purpose of this study is to develop a new detection method for focal retraction that is one of architectural distortions around skinline. In order to extract the thick mammary gland regions, binarization technique is performed. The top-hat processing based on morphological operators is applied to determine the suspect depressed regions around skinline. In our experiments, we have chosen linear structures in seven. The false positives are eliminated by the features of their sizes and positions. After applying this technique to 17 digitized mammograms, the detection sensitivity was 94% with 2.3 false positives per image. It is concluded that this technique is effective to detect the architectural distortion.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Architectural Distortion / Mammogram / Automated Extraction / Breast Cancer / Computer-aided Diagnosis
Paper # MI2002-70
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Conference Information
Committee MI
Conference Date 2002/11/1(1days)
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Registration To Medical Imaging (MI)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An automated detection of architectural distortions on mammograms
Sub Title (in English)
Keyword(1) Architectural Distortion
Keyword(2) Mammogram
Keyword(3) Automated Extraction
Keyword(4) Breast Cancer
Keyword(5) Computer-aided Diagnosis
1st Author's Name Tomoko Matsubara
1st Author's Affiliation Nagoya Bunri University()
2nd Author's Name Tetsuko Ichikawa
2nd Author's Affiliation Gifu University
3rd Author's Name Takeshi Hara
3rd Author's Affiliation Gifu University
4th Author's Name Hiroshi Fujita
4th Author's Affiliation Gifu University
5th Author's Name Satoshi Kasai
5th Author's Affiliation Konica Corporation
6th Author's Name Tokiko Endo
6th Author's Affiliation National Hospital of Nagoya
7th Author's Name Takuji Iwase
7th Author's Affiliation Aichi Cancer Center Hospital
Date 2002/11/1
Paper # MI2002-70
Volume (vol) vol.102
Number (no) 425
Page pp.pp.-
#Pages 4
Date of Issue