IMAT-ITCR Collaboration: Develop deep learning-based methods to identify subtypes of circulating tumor cells from optical microscope images
IMAT-ITCR 合作:开发基于深度学习的方法,从光学显微镜图像中识别循环肿瘤细胞的亚型
基本信息
- 批准号:10675886
- 负责人:
- 金额:$ 7.19万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-01 至 2023-07-31
- 项目状态:已结题
- 来源:
- 关键词:Administrative SupplementAdvanced Malignant NeoplasmAlgorithmic SoftwareAlgorithmsArchitectureArtificial IntelligenceCell modelCellsClassificationCodeCollaborationsCommunitiesComputer AssistedComputing MethodologiesConsumptionDataData AnalysesData AnalyticsData SetDevelopmentEducational CurriculumEnhancersEnvironmentEquilibriumFractionationFundingGoalsHeadHematoxylinHybridsImageImage AnalysisImage EnhancementIndividualInformaticsKnowledgeLibrariesLocationMachine LearningManualsMapsMasksMethodologyMethodsModelingMorphologic artifactsNeoplasm Circulating CellsNetwork-basedOccupationsOpticsParentsPatternPositioning AttributeProcessProtocols documentationResearchResearch PersonnelResidual stateResolutionResourcesRunningSecurityServicesSignal TransductionSoftware DesignSpeedStainsStructureSystemTechnologyTensorFlowTestingTimeTissue imagingTrainingTumor TissueUpdateVariantVertebral columnVisualizationWorkadaptation algorithmanticancer researchapplication programming interfacebasecell typecellular imagingcomputer infrastructurecomputerized data processingdeep learningdeep learning algorithmexperienceexperimental studyfluid flowfluorescence microscopegenerative adversarial networkhandheld mobile deviceimprovedinformatics toolinnovationlearning strategyloss of functionmicrochipmicroscopic imagingnoveloperationpreservationrestorationsimulationtooluser-friendlyweb services
项目摘要
IMAT-ITCR Collaboration: Develop deep learning-based methods to identify subtypes of circulating tumor
cells from optical microscope images
Project Summary/Abstract
The goal of the parent IMAT project (R21CA240185) is to develop a new platform for fractionation and profiling of CTC
subpopulations and elucidate the metastatic potential of CTCs. Currently, this work requires researchers to record hundreds
of individual microscope images of the cells captured on the microchip, integrate all images with flow fluid simulations,
and analyze three features of the capture cells (including angular position, normalized velocity and shear) for identification
of CTC subtypes. This process is very labor-intensive and time-consuming, as most of the steps rely on manual operations.
The goal of the ITCR project (1U01CA249245) is to develop an informatics platform, iSEE-Cell (image-based Spatial
pattern ExplorEr for Cells), which features a suite of informatics tools for tissue image analysis, visualization, exploration
and spatial modeling at the single-cell level. This proposed Administrative Supplement application in support of
collaboration between IMAT and ITCR-funded projects aims to develop deep learning-based methods to identify subtypes
of CTCs from optical microscope images. The rationale underlying this proposal is that the development of deep learning
methods will provide automatic characterization and classification of CTC captured on HU structured microchips. This
proposed collaborative project will leverage the technologies developed by both projects, which will bring together and
enhance the capabilities of complementary technology platforms and methodologies to advance cancer research. Innovation
of the proposed methods include the following: 1) Identification of multiple subtypes of CTCs using their location
information on an HU microchip without destructive immunostaining analysis; 2) Novel Restore-GAN model to improve
quality of microscope image obtained in CTC capture experiments and enhance predication accuracy for CTC subtypes; 3)
The proposed informatics tools will provide computer-assisted automated tools to empower CTC research with artificial
intelligence. Specific aims include: Aim 1: Using the microscope images and analysis/prediction results (from the IMAT
project) as data input to test whether algorithms to classify different types of cell from tumor tissue images (iSEE-Cell,
developed in the ICTR project) can be applied for microscope images; Aim 2: Apply novel computational methods (Restore-
GAN, developed in the ICTR project) to improve image quality of the images obtained from the IMAT project, and test
whether they can improve prediction accuracy for CTC subtypes; Aim 3: Develop a user-friendly interface to incorporate
the iSEE-Cell platform for analyzing optical/fluorescent microscope images remotely. The ability to automatically
extract/analyze information from captured cells in the microscope images is urgently needed and will dramatically enhance
the throughput and work efficiency of the IMAT project.
IMAT-ITCR合作:开发基于深度学习的方法来识别循环肿瘤亚型
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Deep learning detector for high precision monitoring of cell encapsulation statistics in microfluidic droplets.
- DOI:10.1039/d2lc00462c
- 发表时间:2022-10-25
- 期刊:
- 影响因子:6.1
- 作者:Gardner, Karl;Uddin, Md Mezbah;Linh Tran;Thanh Pham;Vanapalli, Siva;Li, Wei
- 通讯作者:Li, Wei
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Wei Li其他文献
Light Harvesting and Enhanced Performance of Si Quantum Dot/Si Nanowire Heterojunction Solar Cells
硅量子点/硅纳米线异质结太阳能电池的光收集和性能增强
- DOI:
10.1002/ppsc.201500192 - 发表时间:
2016-01 - 期刊:
- 影响因子:0
- 作者:
Ling Xu;Wei Li;Linwei Yu;Kunji Chen - 通讯作者:
Kunji Chen
Wei Li的其他文献
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{{ truncateString('Wei Li', 18)}}的其他基金
Developing a novel disease-targeted anti-angiogenic therapy for CNV
开发针对 CNV 的新型疾病靶向抗血管生成疗法
- 批准号:
10726508 - 财政年份:2023
- 资助金额:
$ 7.19万 - 项目类别:
Integrative genomic and functional genomic studies to connect variant to function for CAD GWAS loci
整合基因组和功能基因组研究,将 CAD GWAS 位点的变异与功能联系起来
- 批准号:
10639274 - 财政年份:2023
- 资助金额:
$ 7.19万 - 项目类别:
The Pathophysiological Role of Cerebellar Glia in Rett Syndrome
小脑胶质细胞在 Rett 综合征中的病理生理学作用
- 批准号:
10183494 - 财政年份:2021
- 资助金额:
$ 7.19万 - 项目类别:
The role and mechanism of necrosis in glioblastoma
坏死在胶质母细胞瘤中的作用和机制
- 批准号:
10097263 - 财政年份:2021
- 资助金额:
$ 7.19万 - 项目类别:
The role and mechanism of necrosis in glioblastoma
坏死在胶质母细胞瘤中的作用和机制
- 批准号:
10330992 - 财政年份:2021
- 资助金额:
$ 7.19万 - 项目类别:
The Pathophysiological Role of Cerebellar Glia in Rett Syndrome
小脑胶质细胞在 Rett 综合征中的病理生理学作用
- 批准号:
10591567 - 财政年份:2021
- 资助金额:
$ 7.19万 - 项目类别:
The role and mechanism of necrosis in glioblastoma
坏死在胶质母细胞瘤中的作用和机制
- 批准号:
10553723 - 财政年份:2021
- 资助金额:
$ 7.19万 - 项目类别:
The Pathophysiological Role of Cerebellar Glia in Rett Syndrome
小脑胶质细胞在 Rett 综合征中的病理生理学作用
- 批准号:
10380144 - 财政年份:2021
- 资助金额:
$ 7.19万 - 项目类别:
A new drug entity for combination therapy of diabetic retinopathy
糖尿病视网膜病变联合治疗的新药物实体
- 批准号:
10255782 - 财政年份:2021
- 资助金额:
$ 7.19万 - 项目类别:
Regio- and Enantioselective Alkene Difunctionalizations for the Synthesis of Bioactive Molecules.
用于合成生物活性分子的区域选择性和对映选择性烯烃双官能化。
- 批准号:
10046958 - 财政年份:2020
- 资助金额:
$ 7.19万 - 项目类别: