CADe tools for early detection of breast cancer

U. Bottigli; P. G. Cerello; P. Delogu; M. E. Fantacci; F. Fauci; G. Forni; B. Golosio; A. Lauria; E. Lopez; R. Magro; G. L. Masala; P. Oliva; R. Palmiero; G. Raso; A. Retico; S. Stumbo; S. Tangaro

arXiv · physics/0410082

CADe tools for early detection of breast cancer

U. Bottigli·P. G. Cerello·P. Delogu·M. E. Fantacci·F. Fauci·G. Forni·B. Golosio·A. Lauria·E. Lopez·R. Magro·G. L. Masala·P. Oliva·R. Palmiero·G. Raso·A. Retico·S. Stumbo·S. Tangaro

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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.

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U. Bottigli, P. G. Cerello, P. Delogu, M. E. Fantacci, F. Fauci, G. Forni, B. Golosio, A. Lauria, E. Lopez, R. Magro, G. L. Masala, P. Oliva, R. Palmiero, G. Raso, A. Retico, S. Stumbo, S. Tangaro. 2004-10-13. CADe tools for early detection of breast cancer. https://arxiv.org/abs/physics/0410082

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