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Microcalcifications clusters are subtle signs of breast cancer and are very difficult to diagnose in the mammographic images because of their small size and low contrast with respect to the normal breast tissue. In this paper, we propose an automatic procedure for the identification of microcalcifications clusters to aid the radiologist in the detection of this kind of breast cancer signs.
The paper presents a first implementation of a novel tool to assist radiologists in analyzing screening mammographic images. The software named Assisted Breast Cancer Diagnosis Environment (ABCDE) is able to acquire DICOM images (also in presence of Grayscale Softcopy Presentation State). It is designed to assist the doctor, as a second reader, during the various phases of the diagnosis. The program...
Radiologists that analyze screening mammographic images miss the 10-20% of the diagnosis since this kind of images are very difficult to interpret. In this paper, we present the first step of a CADx (computer aided diagnosis) system that, from the original mammogram, extracts suspicious regions on which the radiologists have to focus their attention. The procedure often successes also in case of very...
In this paper we consider uncertainty handling and propagation by means of RFV through a Computer Aided Detection (CAD) system for denoising and contrast enhancement of mammographic images. In this context, we assume that uncertainty associated to each pixel of the image has both a random and a not negligible systematic contribution. So, after a noise variance estimation performed on the original...
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