MRI: Development of High-Throughput ad High-Resolution Three-Dimensional Tissue Scanner with Internet-Connected 3D Virtual Microscope for Large-Scale Automated Histology
MRI:开发高通量和高分辨率三维组织扫描仪以及联网的 3D 虚拟显微镜,用于大规模自动化组织学
基本信息
- 批准号:1337983
- 负责人:
- 金额:$ 34.16万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-09-01 至 2017-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The objective of this program is to develop a high-throughput and high-resolution 3D tissue scanner with an Internet-connected 3D virtual microscope for large-scale automated histology. The instrument will digitize a wide variety of organs and generate 3D data sets. A data processing pipeline will automatically convert the raw data sets into aligned volumetric data sets without human intervention. Therefore immediate access to the large-scale histological data will be possible for a wide variety of research and research training communities. The intellectual merit is as follows. Large-scale output data of the instrument will be easily acquired and shared through the fast scanner, data processing pipelines, and web-based visualization framework. In the past, investigation of biological organs were limited to either gross system-level studies or highly detailed microscopic analysis of small subsets of the organ. The new tissue scanner will digitally restore tissue structure in 3D with a specialized visualization framework that helps researchers to fully understand function of biological organs. The broader impacts are three folds: (1) Obtaining digitized high-resolution data for multi-scale investigation of biological organs at a high acquisition rate will open up new areas of research in the community. (2) For education infrastructure, microscopic atlases of whole biological organs can serve as educational materials for students and educators at all levels. (3) For dissemination, the project results will provide research communities with a new 3D tissue scanner with a virtual microscope by which researchers can obtain digitized 3D tissue data in sub-micron level resolution from a tissue sample.
该计划的目标是开发一种高通量和高分辨率的3D组织扫描仪,该扫描仪具有互联网连接的3D虚拟显微镜,用于大规模自动组织学。该仪器将模拟各种器官并生成3D数据集。数据处理管道将自动将原始数据集转换为对齐的体积数据集,而无需人工干预。因此,各种各样的研究和研究培训社区将有可能立即获得大规模的组织学数据。其学术价值如下。通过快速扫描仪、数据处理管道和基于Web的可视化框架,可以轻松获取和共享仪器的大规模输出数据。过去,生物器官的研究仅限于系统水平的总体研究或器官小子集的高度详细的显微镜分析。新的组织扫描仪将通过专门的可视化框架以3D方式数字化恢复组织结构,帮助研究人员充分了解生物器官的功能。更广泛的影响有三个方面:(1)以高采集率获得用于生物器官多尺度调查的数字化高分辨率数据将开辟社区研究的新领域。(2)在教育基础设施方面,整个生物器官的显微图集可作为各级学生和教育工作者的教材。(3)为了传播,该项目的成果将为研究界提供一种新的三维组织扫描仪,该扫描仪带有虚拟显微镜,研究人员可以通过该显微镜从组织样本中获得亚微米级分辨率的数字化三维组织数据。
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)
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Jaerock Kwon其他文献
Reduced resolution lane detection algorithm
降低分辨率车道检测算法
- DOI:
10.1109/afrcon.2017.8095697 - 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Li Dang;G. Tewolde;Xiaoyuan Zhang;Jaerock Kwon - 通讯作者:
Jaerock Kwon
Affordable Remote Health Monitoring System for the Elderly Using Smart Mobile Device
使用智能移动设备为老年人提供经济实惠的远程健康监测系统
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
M. Clark;Jongil Lim;G. Tewolde;Jaerock Kwon - 通讯作者:
Jaerock Kwon
Integrated Framework of Autonomous Vehicle with Traffic Sign Recognition in Simulation Environment
仿真环境下自动驾驶汽车与交通标志识别的集成框架
- DOI:
10.1109/eit48999.2020.9208241 - 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
N. Prabhu;Sewoong Min;Haewoon Nam;G. Tewolde;Jaerock Kwon - 通讯作者:
Jaerock Kwon
Image Prediction for Lane Following Assist using Convolutional Neural Network-based U-Net
使用基于卷积神经网络的 U-Net 进行车道跟随辅助图像预测
- DOI:
10.1109/icaiic54071.2022.9722658 - 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
B. Choi;Jaerock Kwon;Haewoon Nam - 通讯作者:
Haewoon Nam
Charting out the octopus connectome at submicron resolution using the knife-edge scanning microscope
- DOI:
10.1186/1471-2202-11-s1-p136 - 发表时间:
2010-07-20 - 期刊:
- 影响因子:2.300
- 作者:
Yoonsuck Choe;Louise C Abbott;Giovanna Ponte;John Keyser;Jaerock Kwon;David Mayerich;Daniel Miller;Donghyeop Han;Anna Maria Grimaldi;Graziano Fiorito;David B Edelman;Jeffrey L McKinstry - 通讯作者:
Jeffrey L McKinstry
Jaerock Kwon的其他文献
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{{ truncateString('Jaerock Kwon', 18)}}的其他基金
MRI: Acquisition of Autonomous Plug-In Hybrid Vehicle Platform for Multidisciplinary Research and Education at the University of Michigan-Dearborn
MRI:收购密歇根大学迪尔伯恩分校用于多学科研究和教育的自主插电式混合动力汽车平台
- 批准号:
2214830 - 财政年份:2022
- 资助金额:
$ 34.16万 - 项目类别:
Standard Grant
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