Computer aids to mammographic diagnosis.
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.
Gale
A G
AG
Department of Radiology, University Hospital, Nottingham.
Roebuck
E J
EJ
Riley
P
P
Worthington
B S
BS
D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D008327:Mammography / Q000379:methods*; D011237:Predictive Value of Tests; D011857:Radiographic Image Interpretation, Computer-Assisted