Publications by authors named "Boris Novak"
Article Synopsis
- The study aimed to evaluate a computer-aided classification (CAC) system for identifying lesions in the BI-RADS category 3 based on mammogram images.
- The CAC system analyzed 106 lesions, utilizing quantitative features from digitized mammograms to determine malignancy likelihood; results showed high sensitivity (94%) and decent specificity (78%), indicating effective classification.
- Ultimately, the CAC system successfully upgraded the classification of 90% of malignant lesions initially categorized as probably benign, showing potential for improving diagnostic accuracy in breast cancer detection.
The Breast Imaging Reporting and Data System (BI-RADS) was implemented to standardize characterization of mammographic findings. The purpose of the present study was to evaluate in which BI-RADS categories the changes recommended by computerized mammographic analysis are most beneficial. Archival cases including, 170 masses (101 malignant, 69 benign) and 63 clusters of microcalcifications (MCs; 36 malignant, 27 benign), were evaluated retrospectively, using the BI-RADS categories, by several radiologists, blinded to the pathology results.
View Article and Find Full Text PDFRationale And Objectives: The purpose of this study was to determine whether the size of mammographically detected microcalcifications is predictive of malignancy.
Materials And Methods: Two hundred sixty mammograms showing clustered microcalcifications with proven diagnoses (160 malignant, 100 benign) were respectively reviewed by experienced mammographers. Lesions that were obviously benign in appearance were excluded from the study.