Journal article
Prediction of near-term risk of developing breast cancer using computerized features from bilateral mammograms
Computerized medical imaging and graphics, Vol.38(5), pp.348-357
07/2014
DOI: 10.1016/j.compmedimag.2014.03.001
PMID: 24725671
Abstract
Asymmetry of bilateral mammographic tissue density and patterns is a potentially strong indicator of having or developing breast abnormalities or early cancers. The purpose of this study is to design and test the global asymmetry features from bilateral mammograms to predict the near-term risk of women developing detectable high risk breast lesions or cancer in the next sequential screening mammography examination. The image dataset includes mammograms acquired from 90 women who underwent routine screening examinations, all interpreted as negative and not recalled by the radiologists during the original screening procedures. A computerized breast cancer risk analysis scheme using four image processing modules, including image preprocessing, suspicious region segmentation, image feature extraction, and classification was designed to detect and compute image feature asymmetry between the left and right breasts imaged on the mammograms. The highest computed area under curve (AUC) is 0.754±0.024 when applying the new computerized aided diagnosis (CAD) scheme to our testing dataset. The positive predictive value and the negative predictive value were 0.58 and 0.80, respectively.
Details
- Title: Subtitle
- Prediction of near-term risk of developing breast cancer using computerized features from bilateral mammograms
- Creators
- Wenqing Sun - Department of Electrical and Computer Engineering, University of Texas, El Paso, TX, United StatesBin Zheng - School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, United StatesFleming Lure - Department of Electrical and Computer Engineering, University of Texas, El Paso, TX, United StatesTeresa Wu - School of Computing, Informatics, Decision Systems Engineering, Arizona State University, AZ, United StatesJianying Zhang - Department of Biology, University of Texas, El Paso, TX, United StatesBenjamin Y Wang - Radiology Department, Sierra Providence Health Network, El Paso, TX, United StatesEdward C Saltzstein - University Breast Care Center at the Texas Tech University Health Sciences, El Paso, TX, United StatesWei Qian - Department of Electrical and Computer Engineering, University of Texas, El Paso, TX, United States
- Resource Type
- Journal article
- Publication Details
- Computerized medical imaging and graphics, Vol.38(5), pp.348-357
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.compmedimag.2014.03.001
- PMID
- 24725671
- ISSN
- 0895-6111
- eISSN
- 1879-0771
- Language
- English
- Date published
- 07/2014
- Academic Unit
- Radiation Oncology
- Record Identifier
- 9984047990002771
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