6533b81ffe1ef96bd12770f1

RESEARCH PRODUCT

A Fuzzy Logic C-Means Clustering Algorithm to Enhance Microcalcifications Clusters in Digital Mammograms

Donato CascioFrancesco FauciR. MagroGiuseppe RasoLetizia Vivona

subject

C-meanCOMPUTER-AIDED DETECTIONComputer scienceCADFuzzy logicSet (abstract data type)Cluster (physics)medicineMammographycancerComputer visionCLASSIFICATION.Cluster analysisbreastmedicine.diagnostic_testbusiness.industryPattern recognitionImage enhancementComputer aided detectionSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)microcalcificationComputingMethodologies_PATTERNRECOGNITIONbreast; cancer; microcalcifications; clustering; fuzzy logic; C-means; COMPUTER-AIDED DETECTION; CLASSIFICATION.Artificial intelligencefuzzy logicbusinessclustering

description

The detection of microcalcifications is a hard task, since they are quite small and often poorly contrasted against the background of images. The Computer Aided Detection (CAD) systems could be very useful for breast cancer control. In this paper, we report a method to enhance microcalcifications cluster in digital mammograms. A Fuzzy Logic clustering algorithm with a set of features is used for clustering microcalcifications. The method described was tested on simulated clusters of microcalcifications, so that the location of the cluster within the breast and the exact number of microcalcifications is known.

yearjournalcountryeditionlanguage
2011-10-01
10.1109/nssmic.2011.6152551http://hdl.handle.net/10447/61705