STTR Phase I: Development and Validation of Noninvasive High-Fidelity Serial Aneurysm Diagnostic Software

STTR 第一阶段：无创高保真串行动脉瘤诊断软件的开发和验证

• 批准号: 2014339
• 负责人: Ali Bakhshinejad
• 金额: $ 22.5万
• 依托单位: VASOGNOSIS, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-15 至 2021-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2014339&HistoricalAwards=false
• 关键词: STTR; Phase; Development; Validation; Noninvasive

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to enable accurate and efficient diagnosis of unruptured brain aneurysms. More specifically, it will make it easier for neuroradiologists to diagnose and analyze medical images for patients with unruptured brain aneurysms, as up to 40% are fatal. Unfortunately, complete review of relevant images can take up to 30 minutes. The software will identify regions of interest in images prior to manual review. enabling accelerated diagnosis. This Small Business Innovation Research (SBIR) Phase I project will develop an end-to-end medical image processing software to empower neuroradiologists to better diagnose unruptured brain aneurysms. This project will undertake deep learning using a convolutional neural network to diagnose, monitor, and provide clinical decision support for intracranial aneurysms from MRI or CT scans. This approach will improve noninvasive diagnosis for significant neurological conditions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该小企业技术转让（STTR）I期项目的更广泛影响/商业潜力是能够准确有效地诊断未破裂的脑动脉瘤。 更具体地说，它将使神经放射科医生更容易诊断和分析未破裂脑动脉瘤患者的医学图像，因为高达40%是致命的。不幸的是，完整查看相关图像可能需要长达30分钟。 软件将在手动审查之前识别图像中的感兴趣区域。从而能够加速诊断。这个小型企业创新研究（SBIR）第一阶段项目将开发一个端到端的医学图像处理软件，使神经放射科医生能够更好地诊断未破裂的脑动脉瘤。该项目将使用卷积神经网络进行深度学习，以通过MRI或CT扫描诊断、监测颅内动脉瘤并提供临床决策支持。 该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。