Literature DB >> 12594083

Mammography and computerized decision systems: a review.

Antônio C Roque1, Túlio C S S André.   

Abstract

Computer-aided diagnosis (CAD) systems in mammography have been developed and investigated for several years and recently they have left the research stage to enter the clinical stage. The purpose of this article is to review the present situation of mammography for breast cancer detection and the role played by CAD systems. Results from the recent literature show that CAD systems have the potential to improve the sensitivities of radiologists in the detection of malignant clustered microcalcifications and masses, while keeping specificities at acceptable levels. This leads to the conclusion that CAD systems can be incorporated into clinical practice as a double reading option to radiologists. However, some issues have yet to be tackled for CAD systems to gain better acceptance and more widespread use worldwide.

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Year:  2002        PMID: 12594083     DOI: 10.1111/j.1749-6632.2002.tb04890.x

Source DB:  PubMed          Journal:  Ann N Y Acad Sci        ISSN: 0077-8923            Impact factor:   5.691


  3 in total

Review 1.  Histopathological image analysis: a review.

Authors:  Metin N Gurcan; Laura E Boucheron; Ali Can; Anant Madabhushi; Nasir M Rajpoot; B Yener
Journal:  IEEE Rev Biomed Eng       Date:  2009-10-30

2.  "Hippocrates-mst": a prototype for computer-aided microcalcification analysis and risk assessment for breast cancer.

Authors:  George Spyrou; Smaragda Kapsimalakou; Antonis Frigas; Konstantinos Koufopoulos; Stamatios Vassilaros; Panos Ligomenides
Journal:  Med Biol Eng Comput       Date:  2006-10-27       Impact factor: 2.602

3.  Deep Learning to Distinguish Recalled but Benign Mammography Images in Breast Cancer Screening.

Authors:  Sarah S Aboutalib; Aly A Mohamed; Wendie A Berg; Margarita L Zuley; Jules H Sumkin; Shandong Wu
Journal:  Clin Cancer Res       Date:  2018-10-11       Impact factor: 12.531

  3 in total

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