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
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
关键词:
3-DimensionalAdoptionAlgorithmsAmyloid beta-ProteinAntibodiesArtificial IntelligenceAstrocytesAutomobile DrivingBackBinding ProteinsBiological MarkersBrainBrain imagingCell DensityCell membraneCellsCollaborationsCommunitiesComplexComputer softwareCytoplasmDataData AnalysesData SetDetectionDevelopmentDiseaseFeedbackFutureGenerationsGlial Fibrillary Acidic ProteinHealthHeterogeneityImageImage AnalysisImaging TechniquesImmunohistochemistryIndividualInstitutesLabelLibrariesLocationMapsMicroscopyModelingMorphologyMusNeurologicNeuronsNeurosciencesNuclearOrganOrgan PreservationOutputPatternPositioning AttributeProcessProteinsProteomicsQuality ControlResearch ContractsResolutionRosaniline DyesTechnologyTestingThree-Dimensional ImageThree-Dimensional ImagingThree-dimensional analysisTissue imagingTissuesTrainingalgorithm developmentartificial intelligence algorithmbasebiomarker-drivencell typecellular imagingcomputerized data processingcostdesignextracellularimprovedinsightneuronal cell bodynew technologyprogramsrelating to nervous systemsegmentation algorithmsoftware developmentstatisticssubmicronterabytetissue processingtooluser friendly softwareuser-friendly
中文摘要
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英文摘要
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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会议论文
3D molecular phenotyping of intact brain tissue via high-throughput active immunohistochemistry
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批准号:10266425
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项目类别:
-
资助金额:$64.25万
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财政年份:2019
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负责人:Katherine Cora Ames
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依托单位:
3D molecular phenotyping of intact brain tissue via high-throughput active immunohistochemistry
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批准号:10414097
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项目类别:
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资助金额:$35.03万
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财政年份:2019
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负责人:Katherine Cora Ames
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依托单位:
海外基金