Paper
9 May 2002 Search of microcalcification clusters with the CALMA CAD station
Maria Evelina Fantacci, Ubaldo Bottigli, Pasquale Delogu, Francesco Fauci, Bruno Golosio, Adele Lauria, Rosa Palmiero, Giuseppe Raso, Simone Stumbo, Sabina Tangaro
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Abstract
CALMA (Computer Assisted Library for Mammography), a collaboration among physicists and radiologists, has collected a large database of digitized mammographic images (about 5000) and developed a CAD (Computer Aided Detection) which can be used also for digitization, as archive and to perform statistical analysis. In this work we present the results obtained in the automatic search of microcalcification clusters. Images (18x24 cm2, digitized by a CCD linear scanner with a 85micrometers pitch and 4096 gray levels) are fully characterized: pathological ones have a consistent description with radiologist's diagnosis and histological data; non pathological ones correspond to patients with a follow up of at least three years. The automated microcalcification clusters analysis is made using a hybrid approach containing both algorithms and neural networks by which are extracted the ROIs (Region Of Interest). These ROIs are indicated on the images and a probability of containing a microcalcification cluster is associated to each ROI. The results obtained with this analysis are described in terms of the ROC (Receiver Operating Characteristic) curve, which shows the true positive fraction (sensitivity) as a function of the false positive fraction (1-specificity) obtained varying the threshold level of the ROI selection procedure.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Maria Evelina Fantacci, Ubaldo Bottigli, Pasquale Delogu, Francesco Fauci, Bruno Golosio, Adele Lauria, Rosa Palmiero, Giuseppe Raso, Simone Stumbo, and Sabina Tangaro "Search of microcalcification clusters with the CALMA CAD station", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467091
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Cited by 17 scholarly publications.
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KEYWORDS
Mammography

Computer aided diagnosis and therapy

Databases

Image classification

Tissues

Neural networks

Computer aided design

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