Abstract:Background Existing state-of-the-art “safe zone” prediction methods are statistics-based methods, image-matching techniques, and machine learning methods. Yet, those methods bring a tension between accuracy and interpretability. Purpose To explore the model explanations and estimator consensus for “safe zone” prediction. Material and Methods We collected the pelvic datasets from Orthopaedic Hospital, and a novel acetabular cup detection method is proposed for automatic ROI segmentation. Hybrid priors comprisin… Show more
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