Automated detection method for architectural distortion based on distribution assessment of mammary gland on mammogram

被引：0

作者：

Hara, T. ^{[1
]}

Makita, T. ^{[1
]}

Matsubara, T. ^{[2
,4
,5
]}

Fujita, H. ^{[1
]}

Inenaga, Y. ^{[3
]}

Endo, T.

Iwase, T.

机构：

[1] Gifu Univ, Dept Intelligent Image Informat, Div Regenerat & Adv Med Sci, Grad Sch Med, Gifu, Japan

[2] Nagoya Bunri Univ, Dept Informat Culture, Inazawa, Japan

[3] Konica Minolta Med Graph Inc, Tokyo, Japan

[4] Nagoya Med Ctr, Dept Radiol, Nagoya, Aichi, Japan

[5] Canc Inst Hosp, Dept Breast Surg, Tokyo, Japan

来源：

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY | 2006年 / 1卷

关键词：

Computer-aided diagnosis; Mammogram; Architectural Distortion;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

The clustered microcalcifications and mass are the important findings in interpreting breast cancer, architectural distortion on mammograms as well We have developed the detection algorithm for distorted area based on concentration of mammary gland. However, it was found that the extraction accuracy of mammary gland was not good enough in the visual evaluation. The purpose of this study is to suggest the improvement of extraction method of mammary gland in order to achieve higher sensitivity. The mean curvature, and the combination of shape index and curvedness were performed for extracting of mammary gland in our previous methods. In our new method, the dynamicrange compression was added as the pre-processing before extracting mammary gland by mean curvature. The detection rate at initial pick-up stage was improved by this improvement. It was concluded that our detection method would be effective.

引用

页码：333 / 334

页数：2

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