Kordon F, Maier A, Swartman B, Privalov M, El Barbari JS, Kunze H (2020)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2020
Publisher: Springer
City/Town: Cham
Pages Range: 671-680
Conference Proceedings Title: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
DOI: 10.1007/978-3-030-59725-2_65
The anatomical axis of long bones is an important reference line for guiding fracture reduction and assisting in the correct placement of guide pins, screws, and implants in orthopedics and trauma surgery. This study investigates an automatic approach for detection of such axes on X-ray images based on the segmentation contour of the bone. For this purpose, we use the medically established two-line method and translate it into a learning-based approach. The proposed method is evaluated on 38 clinical test images of the femoral and tibial bone and achieves a median angulation error of 0.19° and 0.33° respectively. An inter-rater study with three trauma surgery experts confirms reliability of the method and recommends further clinical application.
APA:
Kordon, F., Maier, A., Swartman, B., Privalov, M., El Barbari, J.S., & Kunze, H. (2020). Contour-Based Bone Axis Detection for X-Ray Guided Surgery on the Knee. In Martel AL, et al. (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 (pp. 671-680). Lima, PE: Cham: Springer.
MLA:
Kordon, Florian, et al. "Contour-Based Bone Axis Detection for X-Ray Guided Surgery on the Knee." Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention, Lima Ed. Martel AL, et al., Cham: Springer, 2020. 671-680.
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