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A Novel Breast Tissue Density Classification Methodology
- Source :
- © IEEE Transactions on Information Technology in Biomedicine, 2008, vol. 12, p. 55-65, Articles publicats (D-ATC), DUGiDocs – Universitat de Girona, instname, Recercat. Dipósit de la Recerca de Catalunya
- Publication Year :
- 2008
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2008.
-
Abstract
- It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment.
- Subjects :
- medicine.medical_specialty
Breast imaging
Radiography, Medical -- Digital techniques
Automation
Breast cancer
Image texture
medicine
Medical imaging
Humans
Mammography
Segmentation
Breast
Breast -- Radiography
Electrical and Electronic Engineering
skin and connective tissue diseases
Imatgeria mèdica -- Processament
medicine.diagnostic_test
Contextual image classification
business.industry
Bayes Theorem
Mama -- Radiografia
Pattern recognition
General Medicine
Image segmentation
medicine.disease
Imatges -- Segmentació
Computer Science Applications
Bayesian statistical decision
Diagnòstic per la imatge
Estadística bayesiana
Imaging segmentation
Database Management Systems
Diagnostic imaging
Female
Artificial intelligence
Radiology
business
Radiografia mèdica -- Tècniques digitals
Imaging systems in medicine
Biotechnology
Subjects
Details
- ISSN :
- 10897771
- Volume :
- 12
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Information Technology in Biomedicine
- Accession number :
- edsair.doi.dedup.....aa6c8a1956b153519d157924b69e886b