{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T23:16:32Z","timestamp":1788304592815,"version":"build-2803163510"},"publisher-location":"Cham","reference-count":11,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032350459","type":"print"},{"value":"9783032350466","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,8,15]],"date-time":"2026-08-15T00:00:00Z","timestamp":1786752000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,8,15]],"date-time":"2026-08-15T00:00:00Z","timestamp":1786752000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2027]]},"DOI":"10.1007\/978-3-032-35046-6_2","type":"book-chapter","created":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T04:57:37Z","timestamp":1786683457000},"page":"17-24","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Tumor Tracking as\u00a0Point Tracking: CoTracker3 in\u00a0the\u00a0TrackRAD2025 Challenge"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-5360-5368","authenticated-orcid":false,"given":"Felix","family":"Knispel","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6928-4967","authenticated-orcid":false,"given":"Sergios","family":"Gatidis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,15]]},"reference":[{"key":"2_CR1","doi-asserted-by":"crossref","unstructured":"Doersch, C., et al.: TAPIR: tracking any point with per-frame initialization and temporal refinement. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10061\u201310072 (2023)","DOI":"10.1109\/ICCV51070.2023.00923"},{"key":"2_CR2","doi-asserted-by":"crossref","unstructured":"Karaev, N., Makarov, I., Wang, J., Neverova, N., Vedaldi, A., Rupprecht, C.: CoTracker3: simpler and better point tracking by pseudo-labelling real videos. arXiv preprint: arXiv:2410.11831 (2024)","DOI":"10.1109\/ICCV51701.2025.00568"},{"key":"2_CR3","doi-asserted-by":"crossref","unstructured":"Karaev, N., Rocco, I., Graham, B., Neverova, N., Vedaldi, A., Rupprecht, C.: CoTracker: it is better to track together. In: Proceedings of the ECCV (2024)","DOI":"10.1007\/978-3-031-73033-7_2"},{"key":"2_CR4","unstructured":"Ma, J., et al.: MedSAM2: segment anything in 3D medical images and videos. arXiv preprint: arXiv:2504.03600 (2025)"},{"key":"2_CR5","unstructured":"Meta Research: GitHub \u2013 CoTracker3: simpler and better point tracking by pseudo-labelling real videos. https:\/\/github.com\/facebookresearch\/co-tracker"},{"key":"2_CR6","unstructured":"Meta Research: Hugging face \u2013 point tracking with CoTracker3. https:\/\/huggingface.co\/facebook\/cotracker3"},{"key":"2_CR7","unstructured":"Open Source Computer Vision Library: OpenCV Documentation \u2013 fillPoly. https:\/\/docs.opencv.org\/4.x\/d6\/d6e\/group__imgproc__draw.html#ga8c69b68fab5f25e2223b6496aa60dad5"},{"key":"2_CR8","unstructured":"The scikit-image team: scikit-image Documentation \u2013 skimage.measure.find_contours. https:\/\/scikit-image.org\/docs\/0.25.x\/api\/skimage.measure.html#skimage.measure.find_contours"},{"key":"2_CR9","unstructured":"The SciPy community: SciPy documentation \u2013 scipy.interpolate. https:\/\/docs.scipy.org\/doc\/scipy\/reference\/interpolate.html"},{"key":"2_CR10","unstructured":"The TrackRAD2025 organizers: Trackrad 2025. https:\/\/github.com\/LMUK-RADONC-PHYS-RES\/trackrad2025"},{"issue":"7","key":"2_CR11","doi-asserted-by":"publisher","first-page":"e17964","DOI":"10.1002\/mp.17964","volume":"52","author":"Y Wang","year":"2025","unstructured":"Wang, Y., et al.: TrackRAD 2025 challenge dataset: real-time tumor tracking for MRI-guided radiotherapy. Med. Phys. 52(7), e17964 (2025)","journal-title":"Med. Phys."}],"container-title":["Lecture Notes in Computer Science","AI for Real-Time Tumor Tracking in MRI-Guided Radiotherapy and Trauma Procedure Understanding"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-35046-6_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T22:46:23Z","timestamp":1788302783000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-35046-6_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,15]]},"ISBN":["9783032350459","9783032350466"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-35046-6_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,15]]},"assertion":[{"value":"15 August 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}