Background: Mammograms are one of the most effective preventive means for early detection breast cancer.

BACKGROUND Few data have been published on mammography performance in women who are younger than 40 years. METHODS We pooled data from six mammography registries across the United States from the Breast Cancer Surveillance Consortium. We included 117 738 women who were aged 18-39 years when they had their first screening or diagnostic mammogram during 1995-2005 and followed them for 1 year to...

An algorithm was developed in this study, using rule-based fuzzy logic, to enable masses that are hard to recognize or detect in mammograms to become more readily perceptible. Small lesions, such as microcalcifications and other masses that are hard to recognize, especially on film scan mammograms, were processed through segmentation. A total of 40 mammograms were used and they were classified ...

PurposeTo evaluate the stand-alone diagnostic performances of AI-CAD and outcomes detected abnormalities when applied to mammographic interpretation workflow.MethodsFrom January 2016 December 2017, 6499 screening mammograms 5228 women were collected from a single facility. Historic reads three radiologists used as radiologist interpretation. A commercially-available was for analysis. One not in...

This paper describes the prototype for a Europe-wide distributed database of mammograms entitled MammoGrid, which was developed as part of an EU-funded project. The MammoGrid database appears to the user to be a single database, but the mammograms that comprise it are in fact retained and curated in the centres that generated them. Linked to each image is a potentially large and expandable set ...

This paper describes part of a study aimed at developing a computer-based aid for mammogram screening that makes a detailed comparison between mammograms of the same patient acquired at different screenings and detects changes indicative of cancer. The focus is on determining control points in two mammograms; these points are used to put two mammograms into correspondence. The paper details the...

BACKGROUND Computer-aided mammography is rapidly gaining clinical acceptance, but few data demonstrate its actual benefit in the clinical environment. We assessed changes in mammography recall and cancer detection rates after the introduction of a computer-aided detection system into a clinical radiology practice in an academic setting. METHODS We used verified practice- and outcome-related d...

The segmentation of a digital mammogram into breast region and film background is a necessary prerequisite in the computer-assisted diagnosis of mammograms. The segmentation method should be robust enough to handle a wide variety of digital mammograms obtained from different image acquisition systems. In addition, the large size of digitized mammograms requires an efficient image processing sys...

The main goal of this paper is to compare performance of connected component labeling algorithms on grayscale digital mammograms. This study was carried out as a part of a research for improving efficiency and accuracy of diagnosing breast cancer using digital mammograms. Three connected component labeling algorithms developed by Jung-Me Park [8], Kenji Suzuki [16] and Kesheng Wu [9], were used...

Breast skin–air interface and pectoral muscle segmentation are usually first steps in all CAD applications on scanned as well as digital mammograms. Breast skin–air interface segmentation is much more difficult task when performed on scanned mammograms than on digital mammograms. In case of pectoral muscle segmentation, segmentation difficulty of analog and digital mammograms is usually similar...