Gürcan, M. NafiYardımcı, Y.Çetin, A. Enis2016-02-082016-02-081999-10http://hdl.handle.net/11693/27845Date of Conference: 24-28 Oct. 1999Conference name: Proceedings 1999 International Conference on Image ProcessingIn this paper, computer-aided diagnosis of microcalcifications in mammogram images is considered. Microcalcification clusters are an early sign of breast cancer. Microcalcifications appear as single bright spots in mammogram images. We propose an effective method for the detection of these abnormalities. The first step of this method is two-dimensional adaptive filtering. The filtering produces an error image which is divided into overlapping square regions. In each square region, a Gaussianity test is applied. Since microcalcifications have an impulsive appearance, they are treated as outliers. In regions with no microcalcifications, the distribution of the error image is almost Gaussian, on the other hand, in regions containing microcalcification clusters, the distribution deviates from Gaussianity. Using the theory of the influence function and sensitivity curves, we develop a Gaussianity test. Microcalcification clusters are detected using the Gaussianity test. Computer simulation studies are presented.EnglishCalcification (biochemistry)Computer aided analysisComputer aided diagnosisComputer simulationError analysisFunctionsImage analysisOncologySensitivity analysisSignal filtering and predictionGaussianity testsMicrocalcificationMammographyConference Paper10.1109/ICIP.1999.817145