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Scientific data · 2026

The 2024 Brain Tumor Segmentation Challenge Meningioma Radiotherapy (BraTS-MEN-RT) dataset.

СтатьяDatasetНазвание и аннотация: Перевод в очереди
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LaBella Dominic, Schumacher Katherine, Mix Michael, Leu Kevin, McBurney-Lin Shan, Nedelec Pierre, Villanueva-Meyer Javier, Raleigh David R, Shapey Jonathan, Vercauteren Tom, Chia Kazumi, Ivory Marina, Barfoot Theodore, Al-Salihi Omar, Leu Justin, Halasz Lia M, Velichko Yury, Wang Chunhao, Kirkpatrick John P, Floyd Scott R, Reitman Zachary J, Mullikin Trey C, Vaios Eugene J, Bagci Ulas, Sachdev Sean, Hattangadi-Gluth Jona A, Seibert Tyler M, Farid Nikdokht, Puett Connor, Pease Matthew W, Shiue Kevin, Anwar Syed M, Faghani Shahriar, Taylor Peter, Warman Pranav, Albrecht Jake, Jakab András, Moassefi Mana, Chung Verena, Chai Rong, Aristizabal Alejandro, Karargyris Alexandros, Kassem Hasan, Pati Sarthak, Sheller Micah, Maleki Nazanin, Saluja Rachit, Kofler Florian, Schwarz Christopher G, Lohmann Philipp, Vollmuth Phillipp, Gagnon Louis, Adewole Maruf, Hongwei B Li, Kazerooni Anahita Fathi, Tahon Nourel H, Anazodo Udunna, Moawad Ahmed W, Menze Bjoern, Linguraru Marius G, Aboian Mariam, Wiestler Benedikt, Baid Ujjwal, Conte Gian-Marco, Rauschecker Andreas M, Nada Ayman, Abayazeed Aly H, Huang Raymond, de Verdier Maria Correia, Rudie Jeffrey D, Bakas Spyridon, Calabrese Evan

Аннотация

Meningiomas are the most common primary intracranial tumors, frequently requiring radiotherapy as a part of management. Effective radiotherapy planning for meningiomas necessitates accurate and consistent segmentation of target volumes on MRI, a process that is complex, labor-intensive, and dependent on expert expertise. The 2024 Brain Tumor Segmentation Challenge Meningioma Radiotherapy (BraTS-MEN-RT) Dataset addresses this problem by providing the largest multi-institutional collection of systematically annotated radiotherapy planning MRIs for meningiomas. Publicly accessible, this dataset comprises 570 radiotherapy planning 3D T1-weighted post-contrast MRIs at native resolutions, with 500 cases featuring expert-annotated gross tumor volumes (GTV). Annotations follow standardized radiotherapy planning protocols and include both intact and postoperative meningioma cases, ensuring wide clinical relevance. Contributions from seven diverse medical centers across the United States and the United Kingdom enhance the dataset's generalizability. The dataset aims to accelerate the development of automated segmentation methods for radiotherapy planning, improving workflow efficiency, reducing interobserver variability, and ultimately enhancing patient outcomes.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты