Literature DB >> 16837164

Computerized analysis of tissue density effect on missed cancer detection in digital mammography.

Lihua Li1, Zuobao Wu, Angela Salem, Zhao Chen, Li Chen, Florence George, Maria Kallergi, Claudia Berman.   

Abstract

This paper presents a study of the analysis of breast density in missed cancer cases and the effect of tissue density on cancer detection. A total of 100 missed cancer cases were collected. The breast density tissue was segmented with a statistical-based method. A set of tests was then applied to examine: (1) the differences in density between the mammograms at the detected stage and that at missed stage; (2) the density difference between the cancerous mammograms and their contra-lateral normal mammograms in the missed cancer cases; (3) the effect of breast density on CAD cancer detection. The results demonstrate that breast density is an important factor affecting not only radiologist's reading but also CAD performance. In order to improve early detection of breast cancer, a special effort should be directed to the high dense breast cases in CAD system design.

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Year:  2006        PMID: 16837164     DOI: 10.1016/j.compmedimag.2006.05.007

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  1 in total

1.  Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning.

Authors:  Jinhua Wang; Xi Yang; Hongmin Cai; Wanchang Tan; Cangzheng Jin; Li Li
Journal:  Sci Rep       Date:  2016-06-07       Impact factor: 4.379

  1 in total

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