Automated detection of masses in mammograms by local adaptive thresholding.
In this paper, an algorithm for detection of suspicious masses from mammographic images is presented. The proposed algorithm was tested on a database of 61 mammograms on which masses had previously been marked by experienced radiologists. Results show that the proposed method exhibits for mass detection, a sensitivity of 95.91%. The area under receiver operating characteristic (ROC) Az was 0.946 when enhancement of the original image was performed before detection and 0.938 otherwise. Furthermore in some cases, we could detect some masses that the radiologists were not able to mark out.
Kom
Guillaume
G
LETS, GRETMAT, Ecole Nationale Supérieure Polytechnique, BP 8390, Yaoundé, Cameroun. koguiho@yahoo.fr
Tiedeu
Alain
A
Kom
Martin
M
D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D003936:Diagnosis, Computer-Assisted; D005260:Female; D006801:Humans; D008327:Mammography / Q000706:statistics & numerical data*; D011856:Radiographic Image Enhancement; D012680:Sensitivity and Specificity