Our aim is to establish accurate correspondences between temporal mammograms in order to improve the detection of tumours. We propose a method for detecting abnormalities after aligning a pair of mammograms using thin-plate spline interpolation based on corresponding points on the breast boundary. We also suggest a method for the automatic detection of landmarks within the breast tissue. We sho...

We present first results from a new automated algorithm for the volumetric measurement of the composition of breast tissue from digital mammograms. The new algorithm overcomes issues in previous implementations through better segmentation and use of additional information We measure the success of the new algorithm using an overall quality metric based upon the results from a large multi-site, ...

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...