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Electrical Engineering and Systems Science > Image and Video Processing

arXiv:2304.07248 (eess)
[Submitted on 14 Apr 2023 (v1), last revised 31 May 2024 (this version, v4)]

Title:The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset

Authors:Jeffrey D. Rudie, Rachit Saluja, David A. Weiss, Pierre Nedelec, Evan Calabrese, John B. Colby, Benjamin Laguna, John Mongan, Steve Braunstein, Christopher P. Hess, Andreas M. Rauschecker, Leo P. Sugrue, Javier E. Villanueva-Meyer
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Abstract:The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) dataset is a public, clinical, multimodal brain MRI dataset consisting of 560 brain MRIs from 412 patients with expert annotations of 5136 brain metastases. Data consists of registered and skull stripped T1 post-contrast, T1 pre-contrast, FLAIR and subtraction (T1 pre-contrast - T1 post-contrast) images and voxelwise segmentations of enhancing brain metastases in NifTI format. The dataset also includes patient demographics, surgical status and primary cancer types. The UCSF-BSMR has been made publicly available in the hopes that researchers will use these data to push the boundaries of AI applications for brain metastases. The dataset is freely available for non-commercial use at this https URL
Comments: 15 pages, 2 tables, 2 figures
Subjects: Image and Video Processing (eess.IV); Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2304.07248 [eess.IV]
  (or arXiv:2304.07248v4 [eess.IV] for this version)
  https://doi.org/10.48550/arXiv.2304.07248
Journal reference: Radiology: Artificial Intelligence. 2024;6(2):e230126
Related DOI: https://doi.org/10.1148/ryai.230126

Submission history

From: Jeffrey Rudie [view email]
[v1] Fri, 14 Apr 2023 16:53:06 UTC (2,319 KB)
[v2] Wed, 19 Apr 2023 22:19:30 UTC (2,321 KB)
[v3] Mon, 5 Feb 2024 21:11:40 UTC (2,378 KB)
[v4] Fri, 31 May 2024 01:37:03 UTC (2,378 KB)
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