Toward confident prostate cancer detection using ultrasound: a multi-center study

Paul F. R. Wilson, Mohamed Harmanani, Minh Nguyen Nhat To, Mahdi Gilany, Amoon Jamzad, Fahimeh Fooladgar, Brian Wodlinger, Purang Abolmaesumi, Parvin Mousavi

Abstract: Deep learning-based analysis of micro-ultrasound images to detect cancerous lesions is a promising tool for improving prostate cancer (PCa) diagnosis. An ideal model should confidently identify cancer while responding with appropriate uncertainty when presented with out-of-distribution inputs that arise during deployment due to imaging artifacts and the biological heterogeneity of patients and prostatic tissue.