Infrastructure automation for connectomic image analysis

连接组图像分析的基础设施自动化

• 批准号: 10547607
• 负责人: Thomas Macrina
• 金额: $ 33.46万
• 依托单位: ZETTA AI, LLC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2024-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10547607
• 关键词: Artificial Intelligence; Automation; BRAIN initiative; Basic Science; Brain; Brain Diseases; Caenorhabditis elegans; Client; Code; Communities; Courtship; Data; Data Set; Defect; Detection; Drosophila genus; Electron Microscope; Electron Microscopy; Encapsulated; Engineering; Goals; Gold; Human; Image; Image Analysis; Infrastructure; Ingestion; Institutes; Internet; Manuals; Maps; Mining; Mission; Nerve; Nervous system structure; Pathology; Phase; Private Sector; Process; Recording of previous events; Reporting; Research; Running; Schedule; Semantics; Speed; Synapses; System; Testing; Three-Dimensional Image; Untranslated RNA; Visual; analysis pipeline; base; cloud storage; computational pipelines; connectome; convolutional neural network; cost; data acquisition; data format; insight; medical schools; microscopic imaging; millimeter; neural circuit; operation; petabyte; prevent; reconstruction; success; transmission process

The BRAIN 2025 report states that a major goal of the US BRAIN Initiative is "Generate circuit diagrams," and identifies electron microscopy (EM) as "the gold standard for circuit mapping." So far EM is the only approach that has ever delivered a connectome, a map of all synaptic connections in a nervous system or brain. After the C. elegans connectome in the 1980s, the labor of manual image analysis prevented the EM approach from generalizing to larger nervous systems. Since then, labor has been dramatically reduced by progress in artificial intelligence. Humans need only correct the errors that remain in an automated reconstruction. Zetta AI was founded to make connectomic image analysis accessible to any neuroscientist. In 2021, Zetta completed an automated reconstruction of a cubic millimeter cortical volume for the Allen Institute. This is one of only three existing petascale reconstructions in the world. For the Harvard Medical School, Zetta also completed an automated reconstruction of the Drosophila ventral nerve cord. These successes establish Zetta as a leading organization in connectomics. Zetta’s image analysis pipeline requires significant engineering labor to operate. Based on our operations over the past two years, we have identified several opportunities for engineering labor reduction by process automation, including EM image ingestion, image alignment, and hard example mining. Such process automation will help make connectomics accessible to all neuroscientists. Availability of neural circuit diagrams will aid the discovery of connectopathies and other structural pathologies that have long been hypothesized to be associated with brain disorders.

大脑2025报告指出，美国大脑计划的主要目标是“产生电路图”，并且 将电子显微镜（EM）识别为“电路映射的金标准”。到目前为止是唯一的方法 这曾经提供过连接组，这是神经系统或大脑中所有突触连接的地图。后 秀丽隐杆线虫连接在1980年代，手动图像分析的劳动阻止了EM的方法 概括更大的神经系统。从那以后，通过进步大大降低了劳动 人工智能。人类只需要纠正保留在自动重建中的错误。 Zetta ai 成立是为了使任何神经科学家都可以访问连接组图像分析。 2021年，Zetta完成了 艾伦学院的立方毫米皮质体积的自动重建。这是唯一的 世界上有三项现有的Petascale重建。在哈佛医学院，Zetta还完成了 果蝇腹神经绳的自动重建。这些成功确立了Zetta作为领导 连接组学的组织。 Zetta的图像分析管道需要大量的工程劳动才能运作。 根据过去两年的运营，我们已经确定了工程劳动的几个机会 通过过程自动化的减少，包括EM图像摄入，图像对齐和硬示例挖掘。 这种过程自动化将有助于使所有神经科学家访问连接组学。神经科学家的可用性 电路图将有助于发现连通性途径和其他长期以来的结构病理 假设与脑疾病有关。