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AI-driven biomarker analysis of intact whole brains imaged at micron and sub-micron resolution

AI-driven biomarker analysis of intact whole brains imaged at micron and sub-micron resolution
以微米和亚微米分辨率成像的完整全脑的人工智能驱动生物标志物分析
批准号:
10330017
负责人:
Katherine Cora Ames
金额:
$22.06万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-02-01 至 2023-01-31

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Abstract. Whole-organ 3D immunohistochemistry is revolutionizing the field of neuroscience, enabling unprecedented insight into the distribution of neural cells and neurological markers throughout the brain in health and disease. LifeCanvas Technologies is at the forefront of the new field of spatial proteomics, providing a complete workflow for whole-organ preservation, tissue clearing, immunohistochemical labeling, and imaging. Nevertheless, an ongoing challenge for such studies is the need to rapidly, reproducibly and rigorously quantify terabyte-sized datasets from whole-organ imaging efforts. While progress has been made in applying Artificial Intelligence (AI) tools to enable detection of cellular and sub-cellular markers in neural tissue, one-size-fits-all algorithms are inadequate for analyzing complex, information-rich brain datasets due to varying biomolecular expression patterns (e.g. nuclear, cytoplasmic, membrane-bound) and region-specific heterogeneities in cell density and neural cell types. However, AI-driven algorithms targeting a subset of labeling patterns can be effective provided the availability of adequate training data. LifeCanvas Technologies LCT is optimally positioned to develop highly accurate algorithms serving a wide range of detection tasks through its access to high volumes of whole-organ image data containing a variety of label expression patterns via its Contract Research Organization and user base. LCT proposes to develop a data analysis program, SmartAnalytics, which will embed a suite of AI algorithms within a user-friendly software package to identify labeled cell locations and characterize morphological features across the whole brain at cellular and sub-cellular resolution. Specifically, LCT will use intact, 3D immunolabeled mouse brains to design AI algorithms to detect labeled cells imaged at cellular resolution and generate further algorithms for the segmentation of labeled features imaged at sub-micron resolution. Data from LCT’s Contract Research Organization and academic collaborations will be continually fed back to improve and expand the library of detection algorithms available within SmartAnalytics, and these developments will drive further customer adoption and enhancement of future versions of the software. SmartAnalytics will guide users through model application, quality-control testing, and the generation of output products such as figures and summary statistics. In summary, SmartAnalytics will be an evolving and user- friendly workflow execution program that enables neuroscientists to take full advantage of their 3D image data, driving new discoveries in brain function, development and disease.
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3D molecular phenotyping of intact brain tissue via high-throughput active immunohistochemistry
  • 批准号:
    10266425
  • 项目类别:
  • 资助金额:
    $64.25万
  • 财政年份:
    2019
  • 负责人:
    Katherine Cora Ames
  • 依托单位:
3D molecular phenotyping of intact brain tissue via high-throughput active immunohistochemistry
  • 批准号:
    10414097
  • 项目类别:
  • 资助金额:
    $35.03万
  • 财政年份:
    2019
  • 负责人:
    Katherine Cora Ames
  • 依托单位:
海外基金