Algorithms for cross-scale integration and analysis

跨尺度集成和分析算法

• 批准号: 10038179
• 负责人: Bruce Fischl
• 金额: $ 26.21万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10038179
• 关键词: 3-Dimensional; Achievement; Algorithms; Anatomic Models; Anatomy; Architecture; Atlases; Autopsy; Blood Vessels; Brain; Brain region; Cognitive; Collaborations; Competence; Cortical Dysplasia; Data; Databases; Detection; Diagnosis; Diffusion; Fiber; Functional Magnetic Resonance Imaging; Genetic Transcription; Geometry; Goals; Histologic; Human; Image; Label; Learning; Light; Location; Magnetic Resonance Imaging; Manuals; Maps; Measures; Microscope; Microscopic; Microscopy; Modeling; Molecular; Motor Cortex; Nature; Network-based; Neurodegenerative Disorders; Neurosciences; Noise; Optical Coherence Tomography; Optics; Population Study; Procedures; Process; Rest; Scanning; Side; Signal Transduction; Slice; Source; Specificity; Stains; Structure; Supervision; Surface; Techniques; Technology; Testing; Three-dimensional analysis; Tissues; Training; Work; attenuation; automated segmentation; base; brain volume; convolutional neural network; deep learning; density; feature extraction; imaging modality; improved; in vivo; network architecture; neuropathology; novel; polarized light; theories; three-dimensional modeling; tool; transcriptome sequencing

Abstract - The vast majority of information that neuroscience has obtained about the microscopic structure of the human brain – the substrate for cognitive competencies and the specific locations of neuropathological processes – has been obtained by the analysis of ex vivo tissue. Historically this involves the decades (if not centuries) old procedure of cutting, staining, mounting and imaging under a microscope. The last two decades have seen stunning advances in imaging and analysis of the human brain. This include advances in microscopic (e.g. CLARITY1, SWITCH), mesoscopic (e.g., polarized light imaging, PLI), optical coherence tomography (OCT), RNA-seq and macroscopic imaging (e.g., MRI). While these techniques have generated huge amounts of new information regarding the structural, molecular, connectomic, genetic and transcriptional nature of the brain, they have thus far had little impact on in vivo analysis. In the same way, while we have made great progress in our ability to localize important brain regions in living subjects, these capabilities have had little impact in microscopy and neuropathology. In this project we seek to use our mesoscopic imaging and analysis tools to remove these barriers and facilitate the flow of information from microscopy to in vivo human studies, as well as in the reverse direction. Examples of the impact of these new abilities would be: using resting-state fMRI networks (rsFMRI) to guide the extraction of neuropathological blocks during autopsy to test network-based theories of various neurodegenerative disease or using predicted vascular distributions and densities to improve the laminar specificity of fMRI.

摘要 - 神经科学获得的绝大多数信息 人脑的显微镜结构 - 认知能力的底物和 神经病理学过程的特定位置 - 已通过体内分析获得 组织。从历史上看，这涉及数十年（如果不是几个世纪）切割，染色， 在显微镜下安装和成像。在过去的二十年中，它已经取得了惊人的进步 在对人脑的成像和分析中。这包括显微镜的进步（例如Clarity1， 开关），介观（例如偏振光成像，PLI），光学相干断层扫描（OCT）， RNA-seq和宏观成像（例如MRI）。这些技术产生了巨大 有关结构，分子，连接瘤，遗传和 到目前为止，它们对体内分析的影响很小。在 同样的方式，尽管我们在将重要的大脑区域定位的能力取得了巨大进步的同时 这些功能对显微镜和神经病理学的影响很小。在这个 我们寻求使用介观成像和分析工具来消除这些障碍和 促进从显微镜到体内人类研究的信息流以及反向 方向。这些新能力的影响的示例将是：使用静止状态fMRI 网络（RSFMRI）指导尸检期间神经病理学的提取以进行测试 各种神经退行性疾病的基于网络的理论或使用预测的血管 分布和密度可改善fMRI的层流特异性。