Next generation axonal quantification and classification using AI

使用人工智能的下一代轴突量化和分类

• 批准号: 10609151
• 负责人: Paul Angstman
• 金额: $ 5.5万
• 依托单位: MICROBRIGHTFIELD, LLC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2022-08-18
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10609151
• 关键词: 3-Dimensional; Acute; Address; Animal Model; Area; Artificial Intelligence; Autopsy; Axon; Biotechnology; Brain Diseases; Classification; Collaborations; Communities; Complex; Computer Assisted; Computer software; Detection; Development; Feasibility Studies; Fiber; Goals; Gold; High Performance Computing; Human; Image; Individual; Knowledge; Laboratories; Learning; Logic; Machine Learning; Methods; Morphology; National Institute of Mental Health; Nature; Neuraxis; Neurodegenerative Disorders; Neurodevelopmental Disorder; Neurosciences Research; Pattern; Pharmacology; Phase; Physiological; Publishing; Research; Research Personnel; Societies; Synapses; System; Technology; Time; Tissues; Transgenic Animals; Validation; Work; automated segmentation; axon injury; base; convolutional neural network; density; fighting; image processing; improved; innovation; insight; microscopic imaging; nervous system disorder; neural network; neuropsychiatric disorder; new technology; next generation; novel; operation; prevent; prototype; reconstruction; research and development; terabyte; treatment strategy; usability

Abstract This Lab to Marketplace project describes the development of HyperAxon™, highly innovative software for performing automated segmentation, tracing, reconstruction and quantitative analysis of all axonal fibers visible in three-dimensional (3D) microscopic images of central nervous system (CNS) areas, even those with extremely high axonal fiber density. Accurate and rigorous analysis of all axonal fibers visible in 3D microscopic images of CNS tissue of non-transgenic and transgenic animal models as well as in human post mortem CNS tissue holds the promise of novel insights into physiological neural network connectivity patterns as well as into the neuropathological underpinnings of alterations in connectivity associated with human neuropsychiatric and neurological disorders. However, this cannot be achieved with contemporary, computer-assisted tracing and reconstruction methods, which currently are the gold standard for investigating axonal fibers, because these methods primarily address tracing and reconstruction of only a limited number of individual axonal fibers. HyperAxon will be based on the highly innovative artificial intelligence technology Learning-based Tracing of Dense Axonal Fibers (LTDAF) that was recently developed at MIT Lincoln Laboratory (MIT LL) (Lexington, MA). This project will build upon the original, lab-built LTDAF technology to create commercial software for wide- spread dissemination of this important new technology. Dissemination of this technology via a Lab to Marketplace commercial product is consistent with NIMH goals and will result in the technology having a significant impact on neuroscience research. The game-changing innovation in HyperAxon is the ability to automatically (i) segment, trace and reconstruct all axonal fibers visible in 3D microscopic images of CNS areas with high axonal fiber density, (ii) identify axonal branch points, (iii) resolve axonal fibers of passage from axonal fibers that make presumptive synapses in target regions, (iv) identify axonal fibers showing acute axonal injury and (v) precisely quantify alterations in number and density of axonal fibers in CNS tissue. Based on published pilot work performed at MIT LL, we are convinced that HyperAxon will be impactful in the field of neuroscience research and will enable substantial advancements in research on alterations in CNS circuitry associated with neurodevelopmental, neuropsychiatric, neurodegenerative and neurological disorders. Ultimately, this will result in an improved basis for developing novel treatment strategies for a wide spectrum of complex brain diseases. In Phase I we will demonstrate feasibility of this novel technology by developing prototype software; work in Phase II will focus on creating the full functionality of HyperAxon for commercial release. We will perform extensive feasibility studies, product validation and usability studies of HyperAxon in close collaboration with MIT LL and our academic collaboration partners. A competing technology is not available.

摘要 本实验室到市场项目描述了HyperAxon™的开发，这是一款高度创新的软件， 对所有可见的轴突纤维进行自动分割、追踪、重建和定量分析 在中枢神经系统（CNS）区域的三维（3D）显微图像中，即使是那些具有极强的神经系统的区域， 高轴突纤维密度。精确和严格的分析所有轴突纤维可见的3D显微图像， 非转基因和转基因动物模型以及人死后CNS组织中的CNS组织 对生理神经网络连接模式的新见解的承诺，以及进入 神经病理学基础的改变，在连接与人类神经精神和 神经系统疾病然而，这无法通过当代的计算机辅助追踪和 重建方法，目前是研究轴突纤维的金标准，因为这些 这些方法主要致力于仅追踪和重建有限数量的单个轴突纤维。 HyperAxon将基于高度创新的人工智能技术 最近在麻省理工学院林肯实验室（MIT LL）（列克星敦，MA）开发的致密轴突纤维（LTAH）。 该项目将建立在原始的，实验室建造的LTSTOM技术，为广泛的商业软件， 传播这项重要的新技术。通过实验室传播这项技术， 市场商业产品与NIMH目标一致，并将导致技术具有 对神经科学研究产生重大影响。HyperAxon的改变游戏规则的创新是能够 （i）自动分割、追踪和重建CNS区域的3D显微图像中可见的所有轴突纤维 具有高轴突纤维密度，（ii）识别轴突分支点，（iii）解析从轴突的通道的轴突纤维 在目标区域中形成假定突触的纤维，（iv）识别显示急性轴突损伤的轴突纤维 和（v）精确定量CNS组织中轴突纤维的数量和密度的变化。基于已发表 在MIT LL进行的试点工作，我们相信HyperAxon将在神经科学领域产生影响 研究，并将使与中枢神经系统相关的中枢神经系统电路改变的研究取得实质性进展。 神经发育障碍、神经精神障碍、神经变性障碍和神经障碍。最终，这将导致 为开发针对广泛复杂脑部疾病的新型治疗策略奠定了更好的基础。 在第一阶段，我们将通过开发原型软件来证明这项新技术的可行性; 第二阶段将专注于为商业发布创建HyperAxon的完整功能。我们将执行 与MIT密切合作，对HyperAxon进行广泛的可行性研究、产品验证和可用性研究 LL和我们的学术合作伙伴。没有竞争技术。