Quantitative histopathology for cancer prognosis using quantitative phase imaging on stained tissues
使用染色组织的定量相位成像进行癌症预后的定量组织病理学
基本信息
- 批准号:10249738
- 负责人:
- 金额:$ 57.63万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-03-16 至 2024-03-15
- 项目状态:已结题
- 来源:
- 关键词:2019-nCoVAcademiaAirArtificial IntelligenceBackBiologyBreath TestsCOVID-19COVID-19 testingCancer PrognosisChemicalsClassificationClinicalClinical MicrobiologyComputer softwareComputersDataDevicesExhalationFluorescenceFluorescence MicroscopyFutureGlassGoalsHistopathologyHomeImageImaging DeviceImaging TechniquesIndividualIndustryInfluenzaInfrastructureInterference MicroscopyLabelLightMapsMeasuresMicroscopeModificationMorphologic artifactsNatureOpticsPatientsPerformancePhasePhotobleachingPhototoxicityPopulationPreparationProceduresPublicationsResearchRunningSalesSlideSpecificityStructureSystemTechnologyTestingTimeTissue StainsTrainingViralVirusVirus Diseasesalgorithm trainingbaseclinical infrastructurecoronavirus diseasecostdeep learningdeep learning algorithmdesignimaging systeminstrumentmonitoring devicenanoscalenew technologynoveloperationpandemic diseaseparticlepoint of carepoint of care testingprototypescreeningtool
项目摘要
Summary
Fast, accurate, and scalable testing has been recognized unanimously as crucial for mitigating the
impact of COVID-19 and future pandemics. We propose a technology that allows rapid (~2
minutes) testing for SARS CoV-2. Our technology combines novel label-free imaging and
dedicated deep-learning algorithms to detect and classify viral populations in exhaled air. If
successful, this project will result in a device based on quantitative phase imaging and integrated
AI tools, which will detect the unlabeled virus acquired by the patient’s breath condensed on a
microscope slide. Toward this goal, we will advance Spatial Light Interference Microscopy
(SLIM), an ultrasensitive label-free imaging technique, proven to measure structures down to the
sub-nanometer scale. SLIM was developed in the PI’s Lab at UIUC, its original publication
received 490 citations to date, and has been commercialized by Phi Optics (Research Park,
UIUC), with sales across the world in both academia and industry.
Applying the computed fluorescence maps back to the QPI data, we propose to measure
nanoscale features of viral particles, with high specificity, minimal preparation time, and
independent of clinical infrastructure. As a result, the new technology will eventually be ideal for
point-of-care settings, surveillance screening and as a home monitoring device. We anticipate
that our approach will be scalable to other viruses, with new imaging and training data.
总结
快速、准确和可扩展的测试已被一致认为是减轻
COVID-19和未来流行病的影响。我们提出了一种技术,允许快速(~2
检测SARS CoV-2。我们的技术结合了新颖的无标记成像和
专门的深度学习算法来检测和分类呼出空气中的病毒种群。如果
如果成功,该项目将导致基于定量相位成像和集成的设备
人工智能工具,它将检测患者的呼吸凝结在一个
显微镜载玻片。为了实现这一目标,我们将推进空间光干涉显微镜
(SLIM),一种超灵敏的无标记成像技术,被证明可以测量结构,
亚纳米尺度。SLIM是在UIUC的PI实验室开发的,
到目前为止收到了490次引用,并且已经由PhiOptics(ResearchPark,
UIUC),在世界各地的学术界和工业界都有销售。
将计算的荧光图应用于QPI数据,我们建议测量
病毒颗粒的纳米级特征,具有高特异性、最短的制备时间,并且
独立于临床基础设施。因此,这项新技术最终将成为
定点护理设置、监视筛查和作为家庭监测设备。我们预计
我们的方法将可扩展到其他病毒,具有新的成像和训练数据。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Kevin William Eliceiri其他文献
Kevin William Eliceiri的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Kevin William Eliceiri', 18)}}的其他基金
Center for Multiparametric Imaging of Tumor Immune Microenvironments
肿瘤免疫微环境多参数成像中心
- 批准号:
10374450 - 财政年份:2021
- 资助金额:
$ 57.63万 - 项目类别:
Center for Multiparametric Imaging of Tumor Immune Microenvironments
肿瘤免疫微环境多参数成像中心
- 批准号:
10538588 - 财政年份:2021
- 资助金额:
$ 57.63万 - 项目类别:
Quantitative histopathology for cancer prognosis using quantitative phase imaging on stained tissues
使用染色组织的定量相位成像进行癌症预后的定量组织病理学
- 批准号:
10197858 - 财政年份:2019
- 资助金额:
$ 57.63万 - 项目类别:
Quantitative histopathology for cancer prognosis using quantitative phase imaging on stained tissues
使用染色组织的定量相位成像进行癌症预后的定量组织病理学
- 批准号:
9977150 - 财政年份:2019
- 资助金额:
$ 57.63万 - 项目类别:
Acquisition of a Confocal Microscope for R.M Bock Laboratories
为 R.M Bock 实验室购买共焦显微镜
- 批准号:
7794338 - 财政年份:2010
- 资助金额:
$ 57.63万 - 项目类别:
ImageJ as an extensible image processing framework
ImageJ 作为可扩展的图像处理框架
- 批准号:
7939813 - 财政年份:2009
- 资助金额:
$ 57.63万 - 项目类别:
ImageJ as an extensible image processing framework
ImageJ 作为可扩展的图像处理框架
- 批准号:
7853788 - 财政年份:2009
- 资助金额:
$ 57.63万 - 项目类别:
OME-XML: Development of a Data Standard for Biological Light Microscopy
OME-XML:生物光学显微镜数据标准的开发
- 批准号:
7587392 - 财政年份:2008
- 资助金额:
$ 57.63万 - 项目类别:
相似海外基金
Conference: Rethinking how language background is described in academia and beyond
会议:重新思考学术界及其他领域如何描述语言背景
- 批准号:
2335912 - 财政年份:2024
- 资助金额:
$ 57.63万 - 项目类别:
Standard Grant
ADVANCE Catalyst: Virtual Observatory of Culture for Equity in Academia at the University of Puerto Rico Rio Piedras (VoCEA)
ADVANCE Catalyst:波多黎各 Rio Piedras 大学学术界平等文化虚拟观察站 (VoCEA)
- 批准号:
2214418 - 财政年份:2023
- 资助金额:
$ 57.63万 - 项目类别:
Standard Grant
Comprehensive development strategy of modality-specific "intellectual property" and "cultivation" with an eye on "pharmaceutical affairs" in academia drug discovery
学术界新药研发着眼“药事”的模式“知识产权”与“培育”综合发展策略
- 批准号:
23K02551 - 财政年份:2023
- 资助金额:
$ 57.63万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Accelerating Research Advancement for Investigators Underrepresented in Academia
加速学术界代表性不足的研究人员的研究进展
- 批准号:
10746315 - 财政年份:2023
- 资助金额:
$ 57.63万 - 项目类别:
Planning: HBCU-UP: Strengthening Data Science Research Capacity and Education Programs through Academia-Industry Partnership
规划:HBCU-UP:通过学术界与工业界合作加强数据科学研究能力和教育计划
- 批准号:
2332161 - 财政年份:2023
- 资助金额:
$ 57.63万 - 项目类别:
Standard Grant
From Academia to Business: Development of Novel Therapeutics Against HPV-Associated Cancer
从学术界到商界:针对 HPV 相关癌症的新型疗法的开发
- 批准号:
10813323 - 财政年份:2023
- 资助金额:
$ 57.63万 - 项目类别:
Academics4Rail: Building a community of railway scientific researchers and academia for ERJU and enabling a network of PhDs (academia teaming with industry)
Academys4Rail:为ERJU建立铁路科研人员和学术界社区并建立博士网络(学术界与工业界合作)
- 批准号:
10087488 - 财政年份:2023
- 资助金额:
$ 57.63万 - 项目类别:
EU-Funded
Academics4Rail: Building a Community of Railway Scientific Researchers and Academia for ERJU and Enabling a Network of PhDs (Academia Teaming with Industry)
Academys4Rail:为二院建立铁路科研人员和学术界社区并启用博士网络(学术界与工业界合作)
- 批准号:
10102850 - 财政年份:2023
- 资助金额:
$ 57.63万 - 项目类别:
EU-Funded
Exploring the overall picture of industry-academia-government collaboration: A spectrum of knowledge transfer through formal and informal channels
探索产学官合作的整体图景:通过正式和非正式渠道进行的一系列知识转移
- 批准号:
22K01692 - 财政年份:2022
- 资助金额:
$ 57.63万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Fostering Ethical Neurotechnology Academia-Industry Partnerships: A Stakeholder Engagement and Toolkit Development Project
促进道德神经技术学术界与工业界的伙伴关系:利益相关者参与和工具包开发项目
- 批准号:
10655632 - 财政年份:2022
- 资助金额:
$ 57.63万 - 项目类别: