Literature DB >> 3311272

Computer aids to mammographic diagnosis.

A G Gale1, E J Roebuck, P Riley, B S Worthington.   

Abstract

The improvement of mammographic specificity was investigated by means of identifying specific radiological features. Data are presented on the first 500 patients studied who had previously undergone mammography followed by biopsy. The presence of specific mammographic features on each radiograph, first determined by retrospective examination, was entered into a computer database. Subsequent discriminant function analysis demonstrated the importance of a small number of features whose presence could be used in an algorithm to predict diagnostic outcome. Using this algorithm, this feature-identification approach correctly identified 87.6% of benign and 79% of malignant cases. Specificity was improved to 88% as compared with the original radiological diagnosis of 49%. It is argued that this approach is very promising and a computer-assisted diagnosis based on these findings is described.

Entities:  

Mesh:

Year:  1987        PMID: 3311272     DOI: 10.1259/0007-1285-60-717-887

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  2 in total

Review 1.  A review of the PERFORMS scheme in breast screening.

Authors:  Alastair Gale; Yan Chen
Journal:  Br J Radiol       Date:  2020-06-12       Impact factor: 3.039

2.  Multimodality computer-aided breast cancer diagnosis with FFDM and DCE-MRI.

Authors:  Yading Yuan; Maryellen L Giger; Hui Li; Neha Bhooshan; Charlene A Sennett
Journal:  Acad Radiol       Date:  2010-09       Impact factor: 3.173

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.