Skinline detection in digitized mammograms

Wavelet Based Microcalcifications Detection in Digitized Mammograms

Detection of microcalcifications in mammograms has received much attention from researchers and public health practitioners in these last years. The challenge is to quickly and accurately overcome the development of breast cancer which affects more and more women through the world. Microcalcifications appear in a mammogram as fine, granular clusters, which are often difficult to identify in a r...

Fast detection of masses in digitized mammograms

A novel method for fast detection of regions of suspicion (ROS) that contain circumscribed lesions in mammograms is presented. The position and the size of ROS are first recognized with the aid of a Radial-Basis-Function neural network (RBFNN) by performing windowing analysis. Then a set of criteria is employed to these regions to make the final decision concerning the abnormal ones. Accelerate...

Microcalcification Detection in Digitized Mammograms: A Neurobiologically-Inspired Approach

A Computer-Aided Diagnosis (CAD) system is a set of automatic or semi-automatic tools developed to assist radiologists in the detection and/or classification of abnormalities presented in diagnostic images of different modalities. Although on the early phase of research and development CAD systems were criticized by some computer scientists; regardless of this criticism, nowadays’ experimental ...

A Hybrid System for Detection of Masses in Digitized Mammograms

In this paper, a hybrid segmentation method for detection of masses in digitized mammograms has been developed using three parallel approaches: adaptive thresholding method, Gabor filtering and fuzzy entropy feature as a CAD scheme. The algorithm consists of the following steps: a) Preprocessing of the digitized mammograms including identification of region of interest (ROI) as candidate for ma...

Detection of calcifications in digitized mammograms using wavelet packet analysis