1. CADe tools for early detection of breast cancer
- Author
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Bottigli, U., Cerello, P. G., Delogu, P., Fantacci, M. E., Fauci, F., Forni, G., Golosio, B., Lauria, A., Lopez, E., Magro, R., Masala, G. L., Oliva, P., Palmiero, R., Raso, G., Retico, A., Stumbo, S., and Tangaro, S.
- Subjects
Physics - Medical Physics - Abstract
A breast neoplasia is often marked by the presence of microcalcifications and massive lesions in the mammogram: hence the need for tools able to recognize such lesions at an early stage. Our collaboration, among italian physicists and radiologists, has built a large distributed database of digitized mammographic images and has developed a Computer Aided Detection (CADe) system for the automatic analysis of mammographic images and installed it in some Italian hospitals by a GRID connection. Regarding microcalcifications, in our CADe digital mammogram is divided into wide windows which are processed by a convolution filter; after a self-organizing map analyzes each window and produces 8 principal components which are used as input of a neural network (FFNN) able to classify the windows matched to a threshold. Regarding massive lesions we select all important maximum intensity position and define the ROI radius. From each ROI found we extract the parameters which are used as input in a FFNN to distinguish between pathological and non-pathological ROI. We present here a test of our CADe system, used as a second reader and a comparison with another (commercial) CADe system., Comment: 4 pages, Proceedings of the 4th International Symposium on Nuclear and Related Techniques 2003, Vol. unico, pp. d10/1-d10/4 Havana, Cuba
- Published
- 2004