{"ID":3050119,"CreatedAt":"2026-06-04T02:13:16.786527022Z","UpdatedAt":"2026-06-06T10:22:36.014579446Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.04700","arxiv_id":"2606.04700","title":"A New Angle on Bones: Robust Pose Estimation in X-Ray and Ultrasound","abstract":"Measuring the angle between bone structures is a routine task in medical image analysis and provides a key quantitative parameter for diagnosis and treatment planning. Automated methods can reduce time and cost while improving reproducibility. In this work, we address automatic bone pose estimation using a learning-based point candidate proposal followed by a line model to extract axis parameters. Since conventional line models such as least squares are sensitive to outliers, we incorporate false-positive reduction strategies and robust fitting techniques, such as RANSAC and Hough transforms, to improve robustness. We evaluate our method on three clinically relevant paediatric angle estimation tasks: fracture fragment assessment in radiographs and ultrasound and developmental dysplasia of the hip evaluation in ultrasound using the Graf method. Our approach achieves mean errors of $4.1^\\circ$, $5.4^\\circ$, and $5.51^\\circ$, respectively, not only remaining within the expected clinical observer variability, but also significantly outperforming landmark-based methods. Our code and annotations for fracture angle assessment in radiographs are publicly available on GitHub.","short_abstract":"Measuring the angle between bone structures is a routine task in medical image analysis and provides a key quantitative parameter for diagnosis and treatment planning. Automated methods can reduce time and cost while improving reproducibility. In this work, we address automatic bone pose estimation using a learning-bas...","url_abs":"https://arxiv.org/abs/2606.04700","url_pdf":"https://arxiv.org/pdf/2606.04700v1","authors":"[\"Ron Keuth\",\"Christoph Großbröhmer\",\"Franziska Halm\",\"Miriam Johann\",\"Anne-Nele Schröder\",\"Ludger Tüshaus\",\"Mattias P. Heinrich\",\"Lasse Hansen\"]","published":"2026-06-03T10:25:08Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}