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CAD improves detection of inconspicuous colonic polyps, adds little to search for flat colorectal lesions
Computer-aided detection systems show high potential for detecting inconspicuous colonic polyps but provide little help in locating nonpolypoid colorectal lesions, according to research presented Wednesday at the RSNA meeting.
Computer-aided detection systems show high potential for detecting inconspicuous colonic polyps but provide little help in locating nonpolypoid colorectal lesions, according to research presented Wednesday at the RSNA meeting.
Results of a study of 411 patients with three of the most conspicuous types of polyps -- near folds, on folds, and on walls -- showed high sensitivity for all three types, regardless of the polyp's conspicuity.
However, another study in the session, comparing the sensitivity of CT colonoscopies read by human readers with computer-aided diagnoses for detecting nonpolypoid (flat) colorectal lesions, showed that human readers had a 67% detection rate, compared to 56% for CAD.
The study noted, however, that using CAD software may help lower human perceptive errors and reduce reporting time.
Can AI Bolster Breast Cancer Detection in DBT Screening?
January 16th 2025In sequential breast cancer screening with digital breast tomosynthesis (DBT), true positive examinations had more than double the AI case score of true negative examinations and the highest positive AI score changes from previous exams, according to new research.
Mammography Study Suggests DBT-Based AI May Help Reduce Disparities with Breast Cancer Screening
December 13th 2024New research suggests that AI-powered assessment of digital breast tomosynthesis (DBT) for short-term breast cancer risk may help address racial disparities with detection and shortcomings of traditional mammography in women with dense breasts.
