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

基本信息

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

项目摘要

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) 第一阶段项目的更广泛影响/商业潜力是能够准确、高效地诊断未破裂脑动脉瘤。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% 的脑动脉瘤是致命的。遗憾的是，完整审核相关图像可能需要长达 30 分钟的时间。该软件将在手动检查之前识别图像中的感兴趣区域。实现加速诊断。这个小企业创新研究 (SBIR) 第一阶段项目将开发一种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，通过 MRI 或 CT 扫描来诊断、监测颅内动脉瘤并提供临床决策支持。这种方法将改善重大神经系统疾病的无创诊断。该奖项反映了 NSF 的法定使命，并且通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。