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Software for aiding asymmetries detection and classification on digital mammography images

Grant number: 10/13909-9
Support Opportunities:Scholarships in Brazil - Master
Effective date (Start): March 01, 2011
Effective date (End): February 28, 2013
Field of knowledge:Engineering - Biomedical Engineering - Bioengineering
Principal Investigator:Homero Schiabel
Grantee:Renan Caldeira Menechelli
Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil


The increase in the number of new breast cancer detections is also increasing the developments of CAD schemes modules in order to provide better accuracy in mammography diagnosis. However, the most of researches in this field have been designed to detect or to classify primary features in mammographic images, as suspect masses and microcalcifications. Asymmetric regions have been considered secondary factors in the breast cancer diagnosis procedure, although they could alert to the existence of a suspect lesion. Therefore, the purpose of this work is to develop a module of a CAD scheme in order to aid the detection and classification - in accordance to the BI-RADS standards - of suspect volume asymmetries regions in digital mammography images. The methodology should be based on intelligent and automated techniques of image processing as well as artificial neural networks. The result of such a work should be inserted as a module of a mammography CAD scheme of our group, in order to enlarge the set of information to be used in each case classification and improving the diagnosis accuracy.

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Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
MENECHELLI, Renan Caldeira. Characterization of secondary signals in mammographic images by artificial neural networks to aid diagnosis of breast cancer. 2013. Master's Dissertation - Universidade de São Paulo (USP). Escola de Engenharia de São Carlos (EESC/SBD) São Carlos.

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