The appearance of microcalcifications in mammograms is one of the early signs of breast cancer. So, early detection of microcalcification clusters (MCCs) in mammograms can be helpful for cancer diagnosis and better treatment of breast cancer. In this paper a computer method has been proposed to support radiologists in detection MCCs in digital mammography. First, in order to facilitate and impr...

This work aims to propose an interactive method for a iconic and textual annotation of digital mammograms. The suggested annotation tool consists of a semantic network to represent all information about a set of mammograms obtained from experts in a structured manner based on the BIRADS standard, a correlated XML file system for persistence, data exchange and storage, and a graphical user inter...

Most preventive care guidelines recommend that women aged 40 and older receive a mammogram every 1-2 years to screen for breast cancer. While much research has focused on the factors that influence a woman's decision to obtain a mammogram, less is known about the factors that influence a woman to return for subsequent mammograms at regular intervals. The vast majority of positive mammograms tur...

Flu Shots, Mammograms, and the Perception of Probabilities We study individuals’ decisions to decline or accept preventive health care interventions such as flu shots and mammograms. In particular, we analyze the role of perceptions of the effectiveness of the intervention, by eliciting individuals’ subjective probabilities of sickness and survival, with and without the interventions. Responden...

We propose a fully automated algorithm that is able to select a discriminative feature set from a training database via sequential forward selection (SFS), sequential backward selection (SBS), and F-score methods. We applied this scheme to microcalcifications cluster (MCC) detection in digital mammograms for early breast cancer detection. The system was able to select features fully automatical...

Two methods for enhancing the microcalcifications in digitized mammograms are under consideration. First method is based on multifractal approach, and second on modern mathematical morphology. In multifractal approach, from initial mammogram image, a corresponding multifractal “images” are created, from which a radiologist has a freedom to change the level of segmentation in an interactive mann...

Today, mammography is the best method for early detection of breast cancer. Radiologists failed to detect evident cancerous signs in approximately 20% of false negative mammograms. False negatives have been identified as the inability of the radiologist to detect the abnormalities due to several reasons such as poor image quality, image noise, or eye fatigue. This paper presents a framework for...

Reliable diagnosis of abnormalities is often the case that a mammogram of a woman is compared with previous mammograms. The location of the nipple is invaluable in registration, imaging modality fusion, and as a reference point for classifying microcalcification clusters. Therefore, detecting nipple is important for analyze mammogram images. There are many methods for nipple detection, but they...

The detection of the pectoral muscle boundary in the medio-lateral oblique view of mammograms is essential to improving the computer-aided diagnosis of breast cancer. In this study, a shape-based detection method is proposed for accurately extracting the boundary of the pectoral muscle in mammograms. A shape-based enhancement mask is applied to the mammogram and the initial boundary is then def...

Breast cancer is one of the most dangerous, leading and widespread cancers in the world especially in women. For breast analysis, digital mammography is the most suitable tool used to take mammograms for detection of cancer. It has been proved in the literature that if it can be detected at early and initial stages, then there are many chances to cure timely and efficiently. Therefore, initial ...