Out-of-Distribution Detection for Breast Cancer Classification in Point-of-Care Ultrasound Imaging

The author explores different methods for out-of-distribution detection in breast cancer classification using point-of-care ultrasound imaging, emphasizing the importance of reliable assessments and safe classifiers. The main thesis is to compare and evaluate three OOD detection methods - softmax, energy score, and deep ensembles - to enhance the accuracy of breast cancer classification in POCUS images.