Search results for "Microcalcifications"
showing 5 items of 5 documents
Mammographic images segmentation based on chaotic map clustering algorithm
2013
Background: This work investigates the applicability of a novel clustering approach to the segmentation of mammographic digital images. The chaotic map clustering algorithm is used to group together similar subsets of image pixels resulting in a medically meaningful partition of the mammography. Methods: The image is divided into pixels subsets characterized by a set of conveniently chosen features and each of the corresponding points in the feature space is associated to a map. A mutual coupling strength between the maps depending on the associated distance between feature space points is subsequently introduced. On the system of maps, the simulated evolution through chaotic dynamics leads…
A Fuzzy Logic C-Means Clustering Algorithm to Enhance Microcalcifications Clusters in Digital Mammograms
2011
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.
A fourier-based algorithm for micro-calcification enhancement in mammographic images
2008
Breast cancer is the most widespread cancer in women in the world; it manifests mostly in two forms: microcalcifications and massive lesions. These two forms differ in density, size, shape and number. Consequently, there are two different kinds of mammographic CAD algorithms: those for microcalcifications detection, and those for massive lesions detection. The microcalcifications detection is a hard task, since they are quite small and often poorly contrasted against the background, especially in images affected by digitization noise. In a CAD system the ROI Hunter plays an important role, because missed microcalcifications at this level are definitely lost. For this reason, highlighting me…
Computer-aided diagnosis in digital mammography: comparison of two commercial systems
2014
Aim: Within this work, a comparative analysis of two commercial computer-aided detection or diagnosis (CAD) systems, CyclopusCAD® mammo (v. 6.0) produced by CyclopusCAD Ltd (Palermo, Italy) and SecondLook® (v. 6.1C) produced by iCAD Inc. (OH, USA) is performed by evaluating the results of both systems application on an unique set of mammographic digital images routinely acquired in a hospital structure. Materials & methods: The two CAD systems have been separately applied on a sample set of 126 mammographic digital cases, having been independently diagnosed by two senior radiologists. According to the human diagnosis, the cases in the sample reference set are divided into 61 negatives and 6…
Fuzzy technique for microcalcifications clustering in digital mammograms
2012
Abstract Background Mammography has established itself as the most efficient technique for the identification of the pathological breast lesions. Among the various types of lesions, microcalcifications are the most difficult to identify since they are quite small (0.1-1.0 mm) and often poorly contrasted against an images background. Within this context, the Computer Aided Detection (CAD) systems could turn out to be very useful in breast cancer control. Methods In this paper we present a potentially powerful microcalcifications cluster enhancement method applicable to digital mammograms. The segmentation phase employs a form filter, obtained from LoG filter, to overcome the dependence from …