{"ID":2874366,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.05483","arxiv_id":"2509.05483","title":"Veriserum: A dual-plane fluoroscopic dataset with knee implant phantoms for deep learning in medical imaging","abstract":"Veriserum is an open-source dataset designed to support the training of deep learning registration for dual-plane fluoroscopic analysis. It comprises approximately 110,000 X-ray images of 10 knee implant pair combinations (2 femur and 5 tibia implants) captured during 1,600 trials, incorporating poses associated with daily activities such as level gait and ramp descent. Each image is annotated with an automatically registered ground-truth pose, while 200 images include manually registered poses for benchmarking. Key features of Veriserum include dual-plane images and calibration tools. The dataset aims to support the development of applications such as 2D/3D image registration, image segmentation, X-ray distortion correction, and 3D reconstruction. Freely accessible, Veriserum aims to advance computer vision and medical imaging research by providing a reproducible benchmark for algorithm development and evaluation. The Veriserum dataset used in this study is publicly available via https://movement.ethz.ch/data-repository/veriserum.html, with the data stored at ETH Zürich Research Collections: https://doi.org/10.3929/ethz-b-000701146.","short_abstract":"Veriserum is an open-source dataset designed to support the training of deep learning registration for dual-plane fluoroscopic analysis. It comprises approximately 110,000 X-ray images of 10 knee implant pair combinations (2 femur and 5 tibia implants) captured during 1,600 trials, incorporating poses associated with d...","url_abs":"https://arxiv.org/abs/2509.05483","url_pdf":"https://arxiv.org/pdf/2509.05483v1","authors":"[\"Jinhao Wang\",\"Florian Vogl\",\"Pascal Schütz\",\"Saša Ćuković\",\"William R. Taylor\"]","published":"2025-09-05T20:15:43Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","project_urls":"[\"https://movement.ethz.ch/data-repository/veriserum.html\"]","has_code":false,"code_links":[{"ID":610134,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2874366,"paper_url":"https://arxiv.org/abs/2509.05483","paper_title":"Veriserum: A dual-plane fluoroscopic dataset with knee implant phantoms for deep learning in medical imaging","repo_url":"https://github.com/wjh19990923/Veriserum","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}