MRI Acquisition: Advanced Computing Infrastructure Driving long-tail Sciences

MRI 采集：先进计算基础设施推动长尾科学

• 批准号: 1920024
• 负责人: Neranjan Edirisinghe Pathirannehe
• 金额: $ 90万
• 依托单位: Georgia State University Research Foundation, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1920024&HistoricalAwards=false
• 关键词: MRI; Acquisition; Advanced; Computing; Infrastructure

ACIDS (Advanced Computing Infrastructure Driving Long-tail Sciences), supports and enables multidisciplinary research in LTS (Long Tail Science) projects that are not traditionally supported by large scale computing centers. The system whose acquisition is enabled by this award is expected to act as a catalyst for the regional advancement of LTS. The projects combine large collaborations and research programs requiring advanced computing infrastructure to work with the data and perform the latest analyses and simulations. The instrument supports the increase of knowledge in multiple domains since these machine learning methods are data hungry and computationally expensive.The instrumentation advances scientific inquiries to improved antiviral developments, effective public policy decisions, efficient pathological review, and large-scale neuro-imaging data mining. The application of deep learning techniques, structural biology, neuroscience, public health evaluation, language translation, anomaly detection, etc., constitutes a common theme running through these projects. All participating faculty, staff, postdocs, and students across multiple centers and colleges will have access to ACIDS through collaborations and partnerships. Thus, training, outreach, and education will be supported in multiple application areas.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.

ACIDS（Advanced Computing Infrastructure Driving Long-tail Sciences）支持并实现LTS（Long Tail Science）项目中的多学科研究，这些项目传统上不受大型计算中心的支持。通过该奖项获得的系统预计将成为LTS区域发展的催化剂。这些项目结合了联合收割机大型合作和研究项目，需要先进的计算基础设施来处理数据并执行最新的分析和模拟。该仪器支持多个领域的知识增长，因为这些机器学习方法是数据饥饿和计算昂贵的仪器推进科学调查，以改善抗病毒药物的开发，有效的公共政策决策，有效的病理审查，和大规模的神经成像数据挖掘。深度学习技术、结构生物学、神经科学、公共卫生评估、语言翻译、异常检测等的应用，是贯穿这些项目的一个共同主题。所有参与的教师，工作人员，博士后和学生在多个中心和学院将有机会通过合作和伙伴关系获得ACIDS。该奖项反映了NSF的法定使命，并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，被认为值得支持。