ReMIND: The Brain Resection Multimodal Imaging Database.

Parikshit Juvekar, Reuben Dorent, Fryderyk Kögl, Erickson Torio, Colton Barr, Laura Rigolo, Colin Galvin, Nick Jowkar, Anees Kazi, Nazim Haouchine, Harneet Cheema, Nassir Navab, Steve Pieper, William M Wells, Wenya Linda Bi, Alexandra Golby, Sarah Frisken, Tina Kapur
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Abstract

The standard of care for brain tumors is maximal safe surgical resection. Neuronavigation augments the surgeon's ability to achieve this but loses validity as surgery progresses due to brain shift. Moreover, gliomas are often indistinguishable from surrounding healthy brain tissue. Intraoperative magnetic resonance imaging (iMRI) and ultrasound (iUS) help visualize the tumor and brain shift. iUS is faster and easier to incorporate into surgical workflows but offers a lower contrast between tumorous and healthy tissues than iMRI. With the success of data-hungry Artificial Intelligence algorithms in medical image analysis, the benefits of sharing well-curated data cannot be overstated. To this end, we provide the largest publicly available MRI and iUS database of surgically treated brain tumors, including gliomas (n=92), metastases (n=11), and others (n=11). This collection contains 369 preoperative MRI series, 320 3D iUS series, 301 iMRI series, and 356 segmentations collected from 114 consecutive patients at a single institution. This database is expected to help brain shift and image analysis research and neurosurgical training in interpreting iUS and iMRI.

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ReMIND:脑切除多模式成像数据库。
脑肿瘤的护理标准是将最大限度的安全手术切除作为第一步。神经导航增强了外科医生实现这一目标的能力,但随着手术的进行,由于大脑的变化而失去了有效性。此外,许多胶质瘤很难与邻近的健康脑组织区分开来。术中MRI(iMRI)是一种有用的外科辅助手段,可用于显示残余肿瘤和脑转移。术中超声(iUS)也有类似的目的,同时也更快、更容易融入工作流程。然而,与术中MRI相比,它在肿瘤组织和正常脑组织之间提供了较低的对比度。随着渴望数据的人工智能(AI)/机器学习(ML)算法在推进医学图像分析技术方面的成功,共享精心策划的数据的好处怎么强调都不为过。为此,我们在这里提供了最大的公开可用的手术治疗脑肿瘤的MRI和术中超声成像数据库,包括神经胶质瘤(n=92)、转移瘤(n=11)和其他肿瘤(n=11)。该集合包含369个术前MRI系列、320个3D术中超声系列、301个术中MRI系列和356个分割,这些分割来自单个机构的114名连续患者。我们希望这些数据能成为脑转移和图像分析的计算研究以及术中超声和iMRI解释的神经外科训练的资源。
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