Although mammography has proven to be the most reliable and cost‑effective method for the early detection of breast cancer in a screening environment, mammographic interpretation is quite difficult, due to time required, the complexity of tissue patterns, and the low yield. All current CAD schemes use features extracted from images and abnorrnalities at the time when a positive reading was performed. Hence these systems are optimized for the detection of abnorrnalities at the same stage of development as the typical level identified by an experienced reader. In this project we propose to develop and test CAD schemes that focus on optimization of the detection in marnmograms that had been interpreted as negative but the patients were found to have breast cancers on a follow‑up (later) exarnination. This project will not only explore a new approach to detect small and subtle cancers, it may result in great benefit to the patients, since earlier detection of breast aulcer can substantially reduce mortality amd morbidity.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21CA085241-01A1
Application #
6260260
Study Section
Diagnostic Imaging Study Section (DMG)
Program Officer
Liu, Guoying
Project Start
2001-04-01
Project End
2003-03-31
Budget Start
2001-04-01
Budget End
2002-03-31
Support Year
1
Fiscal Year
2001
Total Cost
$150,000
Indirect Cost
Name
University of Pittsburgh
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
053785812
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
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Zheng, Bin; Leader, Joseph K; Abrams, Gordon et al. (2004) Computer-aided detection schemes: the effect of limiting the number of cued regions in each case. AJR Am J Roentgenol 182:579-83
Zheng, Bin; Swensson, Richard G; Golla, Sara et al. (2004) Detection and classification performance levels of mammographic masses under different computer-aided detection cueing environments. Acad Radiol 11:398-406
Zheng, Bin; Good, Walter F; Armfield, Derek R et al. (2003) Performance change of mammographic CAD schemes optimized with most-recent and prior image databases. Acad Radiol 10:283-8
Zheng, Bin; Hardesty, Lara A; Poller, William R et al. (2003) Mammography with computer-aided detection: reproducibility assessment initial experience. Radiology 228:58-62
Chang, Yuan-Hsiang; Good, Walter F; Leader, Joseph K et al. (2003) Integrated density of a lesion: a quantitative, mammographically derived, invariable measure. Med Phys 30:1805-11
Chang, Yuan-Hsiang; Wang, Xiao-Hui; Hardesty, Lara A et al. (2002) Computerized assessment of tissue composition on digitized mammograms. Acad Radiol 9:899-905
Zheng, Bin; Shah, Ratan; Wallace, Luisa et al. (2002) Computer-aided detection in mammography: an assessment of performance on current and prior images. Acad Radiol 9:1245-50