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

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

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


This paper presents a study of the analysis of breast density in missed cancer cases and the effect of tissue density on caner 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.

Original languageEnglish (US)
Pages (from-to)291-297
Number of pages7
JournalComputerized Medical Imaging and Graphics
Issue number5
StatePublished - Jul 2006
Externally publishedYes


  • Breast cancer
  • CAD
  • Detection
  • Mammography
  • Statistical analysis
  • Tissue density

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design


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