This paper presents a novel approach to finding a priori interesting regions in mammograms. We propose a topographic representation called the iso-level contour map consisting of iso-level contours at multiple intensity levels, in order to delineate those regions of interest (ROI’s) in mammograms which appear to be salient. Such salient areas form a dense quasi-concentric pattern of iso-level c...

This paper deals with segmentation of breast anatomical regions, pectoral muscle, fatty and fibroglandular regions, using a Bayesian approach. This work is a part of a computer aided diagnosis project aiming at evaluating breast cancer risk and its association with characteristics (density, texture, etc.) of regions of interest on digitized mammograms. Novelty in this paper consists in applying...

The identification of glandular tissue in breast X-rays (mammograms) is important both in assessing asymmetry between left and right breasts, and in estimating the radiation risk associated with mammographic screening. The appearance of glandular tissue in mammograms is highly variable, ranging from sparse streaks to dense blobs. Fatty regions are generally smooth and dark. Texture analysis pro...

OBJECTIVE To assess the effect of telephone reminders on repeat screening mammogram completion among women who have already had one or more mammograms. METHODS Seven hundred and forty women whose turn came for further mammography and who could be reached by telephone out of 1,372 women registered at a Cancer Screening and Education Center (CSEC) were studied in Erzurum, Turkey, from January t...

AlxtmcfIn this paper, wc prcscr a novel approach to the problem of computer-aided analysis of digital mammograms for breast cancer detection. The algorithm devcloped herc classifics mammograms into norma; & abnormal. First, thc structures in mammograms produced by normal glandular tissue of varying dcnsity are eliminated using a Wavelet Transform (WT) based local averagc subtraction. Then the l...

CADMIUM II is a system for the interpretation of mammograms. A novel aspect of the system is that it combines symbolic reasoning with image processing, in contrast with most other approaches, which use only image processing and rely on artificial neural networks (ANNs) to classify mammograms. A problem of ANNs is that the advice they give cannot be traced back to communicable diagnostic inferen...

This study evaluated the effects of interactive voice response (IVR) system reminders to managed care organization (MCO) members to obtain mammograms, Papanicolaou (Pap) tests, and influenza immunizations. The MCO identified 3 member cohorts and sent IVR reminders to get preventive services. Analyses employed claims data to examine relationships between IVR reminders and preventive service use ...

A digital mammogram generally detects varying degrees of breast cancer such as clustered microcalcifications, speculated lesions, circumscribed masses, ill-defined masses, and architectural distortions. Many methods of analysing digital mammograms have been recently examined and yielded varied success. Common techniques from the field of image processing have been applied to digital mammograms ...

Breast cancer is the second leading cause for death among women and it is diagnosed with the help of mammograms. Oncologists are miserably failed in identifying the micro calcification at the early stage with the help of the mammogram visually. In order to improve the performance of the breast cancer screening, most of the researchers have proposed Computer Aided Diagnosis using image processin...

We have been developing an automated detection algorithm for masses on mammograms. There were the cases of missed detections, in most of which the masses existed around thick-mammarygland region or near chest-wall region. The purpose of this study is to develop an algorithm for detecting such masses based on a sector-shape mass-pattern model. After applying the new technique along with our prev...