A Fully Automatic System For Verified Computerized Stereoanalysis

用于验证计算机立体分析的全自动系统

基本信息

批准号：
8143297
负责人：
PETER Randolph MOUTON
金额：
$ 13.28万
依托单位：
STEREOLOGY RESOURCE CENTER, INC.
依托单位国家：
美国
项目类别：
财政年份：
2003
资助国家：
美国
起止时间：
2003-07-10 至 2013-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8143297
关键词：
Active Learning Address Algorithms Area Biological Biological Process Biomedical Research Blood capillaries Cell Volumes Classification Color Communities Computer software Computer-Assisted Image Analysis Computers Databases Detection Development Disease Doctor of Philosophy Educational workshop Engineering Florida Funding Glass Goals Gold Grant Growth Health Histology Human Human Resources Image Institution International Length Libraries Longevity Machine Learning Manuals Marketing Measurement Methodology Methods Microscopic Microscopy Noise Performance Phase Probability Research Research Project Grants Resources Sales Sampling Savings Scientist Shapes Signal Transduction Slide Small Business Innovation Research Grant Solid Staining method Stains Structure Surface System Technology Testing Texture Therapeutic Time Tissue Stains Tissues Training United States National Institutes of Health Universities Update Vendor Work animal tissue base capillary commercialization computer program computerized cost digital imaging high throughput analysis human disease human tissue improved innovation interest novel strategies novel therapeutic intervention phase 1 study programs public health relevance validation studies

项目摘要

DESCRIPTION (provided by applicant): A Fully Automatic System For Verified Computerized Stereoanalysis SUMMARY The requirement for a trained user to interact with tissue and images is a long-standing impediment to higher throughput analysis of biological microstructures using unbiased stereology, the state-of-the-art method for accurate quantification of biological structure. Phase 1 studies addressed this limitation with Verified Computerized Stereoanalysis (VCS), an innovative approach for automatic stereological analysis that improves throughput efficiency by 6-9 fold compared to conventional computerized stereology. Work in Phase 2 integrated VCS into the Stereologer", an integrated hardware-software-microscopy system for stereological analysis of tissue sections and stored images. Validation studies of first-order stereological parameters. i.e., volume, surface area, length, number, confirmed that the color-based detection methods in the VCS approach achieve accurate results for automatic stereological analysis of high S:N biological microstructures. These studies indicate that fully automatic stereological analysis of tissue sections and stored images can be realized by elimination of two remaining barriers, which will be addressed in this Phase II Continuation Competing Renewal. In Aim 1, applications for feature extraction and microstructure classification, developed in part with funding from the Office of Naval Research, will be integrated into the VCS program. The new application (VCS II) will use these approaches to automatically detect and classify polymorphic microstructures of biological interest using a range of feature calculations, including size, color, border, shape, and texture, with support from active learning and Support Vector Machines. Work in Aim 2 will eliminate physical handling of glass slides during computerized stereology studies by equipping the Stereologer system with automatic slide loading/unloading technology controlled by the Stereologer system. This technology will approximately double the throughput efficiency of the current VCS program and support "human-in-the-loop" interaction for sample microstructures on the border between two or more adjacent classes. The studies in Aim 3 will rigorously test the hypothesis that fully automatic VCS can quantify first- and second-order stereological parameters, without a loss of accuracy compared to the current gold-standard - non-automatic computerized stereology, e.g., manual Stereologer. If these studies validate the accuracy of VCS II, then commercialization of the fully automatic program will facilitate the throughout efficiency for testing scientific hypotheses in a wide variety of biomedical research projects; reduce labor costs for computerized stereology studies; hasten the growth of our understanding of biological processes that underlie health, longevity, and disease; and accelerate the development of novel approaches for the therapeutic management of human disease. Solid evidence that the SRC and its strategic partners can effectively commercialize this technology is demonstrated by their worldwide sales and support of the Stereologer system for the past 13 years. Key personnel and participating institutions: 7 Peter R. Mouton, Ph.D. (PI), Stereology Resource Center, Chester, MD. 7 Dmitry Goldgof, Ph.D., University of South Florida Coll. Engineering, Tampa, Fl. 7 Larry Hall, Ph.D., University of South Florida Coll. Engineering, Tampa, Fl. 7 Joel Durgavich, MS, Systems Planning and Analysis, Alexandria, VA. 7 Kurt Kramer, MS, Computer Programmer, University of South Florida, Coll. Engineering, Tampa, Fl. 7 Michael E. Calhoun, Ph.D., Sinq Systems, Columbia, MD PUBLIC HEALTH RELEVANCE: Many fields of scientific research require a trained expert to make tedious and repetitive measurements of microscopic changes in animal and human tissues. This project will produce a computer program that performs these measurements with equal accuracy to a trained expert, but with dramatic savings in time and costs. Allowing scientists to complete more research in less time will accelerate our understanding of the factors that promote health and longevity, and hasten progress toward the development of new treatments for human diseases.

描述（由申请人提供）：用于经过验证的计算机立体分析的全自动系统摘要要求受过训练的用户与组织和图像交互是使用无偏立体学对生物微结构进行更高通量分析的长期障碍，即现状准确定量生物结构的最先进方法。第一阶段研究通过验证计算机立体分析 (VCS) 解决了这一限制，这是一种自动立体分析的创新方法，与传统计算机立体分析相比，可将吞吐量效率提高 6-9 倍。第二阶段的工作将 VCS 集成到 Stereologer 中，这是一个集成的硬件-软件-显微镜系统，用于组织切片和存储图像的体视学分析。一阶体视学参数的验证研究，即体积、表面积、长度、数量、确认VCS 方法中基于颜色的检测方法可实现高 S:N 生物微观结构的自动体视分析的准确结果。这些研究表明，可以通过消除两个来实现组织切片和存储图像的全自动体视分析。目标 1 中，部分由海军研究办公室资助开发的特征提取和微观结构分类应用程序将被整合到 VCS 计划中。 (VCS II) 将使用这些方法，在主动学习和支持向量机的支持下，通过一系列特征计算（包括尺寸、颜色、边界、形状和纹理）来自动检测和分类具有生物学意义的多态微结构。 Aim 2 的工作将通过为 Stereologer 系统配备由 Stereologer 系统控制的自动载玻片加载/卸载技术，消除计算机体视学研究期间对载玻片的物理处理。该技术将使当前 VCS 程序的吞吐量效率大约提高一倍，并支持两个或多个相邻类别之间边界上的样品微结构的“人机交互”交互。目标 3 中的研究将严格测试以下假设：全自动 VCS 可以量化一阶和二阶体视学参数，与当前的黄金标准 - 非自动计算机化体视学（例如手动 Stereologer）相比，不会损失准确性。如果这些研究验证了VCS II的准确性，那么全自动程序的商业化将提高各种生物医学研究项目中测试科学假设的整体效率；降低计算机体视学研究的劳动力成本；加速我们对构成健康、长寿和疾病的生物过程的理解；并加速开发人类疾病治疗管理的新方法。 SRC 及其战略合作伙伴过去 13 年对 Stereologer 系统的全球销售和支持证明了 SRC 及其战略合作伙伴能够有效地将这项技术商业化的有力证据。主要人员及参与机构： 7 Peter R. Mouton, Ph.D. （PI），体视学资源中心，切斯特，马里兰州。 7 Dmitry Goldgof，博士，南佛罗里达大学学院。工程，佛罗里达州坦帕7 Larry Hall，博士，南佛罗里达大学学院。工程，佛罗里达州坦帕7 Joel Durgavich，理学硕士，系统规划和分析，弗吉尼亚州亚历山大。 7 Kurt Kramer，硕士，计算机程序员，南佛罗里达大学，Coll.工程，佛罗里达州坦帕7 Michael E. Calhoun 博士，Sinq Systems，哥伦比亚，马里兰州公共健康相关性：许多科学研究领域都需要训练有素的专家对动物和人体组织的微观变化进行繁琐且重复的测量。该项目将生成一个计算机程序，该程序可以以与训练有素的专家相同的精度执行这些测量，但可以大大节省时间和成本。让科学家在更短的时间内完成更多的研究将加速我们对促进健康和长寿因素的理解，并加快人类疾病新疗法的开发进展。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Caloric restriction attenuates amyloid deposition in middle-aged dtg APP/PS1 mice.

热量限制减弱了中年 dtg APP/PS1 小鼠的淀粉样蛋白沉积。

DOI：
发表时间：
2009-10-30
期刊：
影响因子：
2.5
作者：
Mouton, Peter R;Chachich, Mark E;Quigley, Christopher;Spangler, Edward;Ingram, Donald K
通讯作者：
Ingram, Donald K

The effects of age and lipopolysaccharide (LPS)-mediated peripheral inflammation on numbers of central catecholaminergic neurons.

年龄和脂多糖（LPS）介导的外周炎症对中枢儿茶酚胺能神经元数量的影响。

DOI：
发表时间：
2012-02
期刊：
影响因子：
4.2
作者：
Mouton, P R;Kelley;Tweedie, D;Spangler, E L;Perez, E;Carlson, O D;Short, R G;deCabo, R;Chang, J;Ingram, D K;Li, Y;Greig, N H
通讯作者：
Greig, N H

Unbiased estimation of cell number using the automatic optical fractionator.

使用自动光学分馏器对细胞数量进行无偏估计。

DOI：
发表时间：
2017-03
期刊：
影响因子：
2.8
作者：
Mouton, Peter R;Phoulady, Hady Ahmady;Goldgof, Dmitry;Hall, Lawrence O;Gordon, Marcia;Morgan, David
通讯作者：
Morgan, David

Automatic section thickness determination using an absolute gradient focus function.

使用绝对梯度聚焦功能自动确定切片厚度。

DOI：
发表时间：
2012-12
期刊：
影响因子：
2
作者：
Elozory, D T;Kramer, K A;Chaudhuri, B;Bonam, O P;Goldgof, D B;Hall, L O;Mouton, P R
通讯作者：
Mouton, P R

Neuron number and size in prefrontal cortex of children with autism.

自闭症儿童前额皮质的神经元数量和大小。

DOI：
10.1001/jama.2011.1638
发表时间：
2011-11-09
期刊：
JAMA
影响因子：
0
作者：
E. Courchesne;P. Mouton;M. Calhoun;K. Semendeferi;Clelia Ahrens‐Barbeau;Melodie J. Hallet;C. Barnes;K. Pierce
通讯作者：
K. Pierce