Quality assessment of 3D volume representation of 2D depth stack digital pathology images through advanced post-processing and quantitative analysis

通过先进的后处理和定量分析对 2D 深度叠加数字病理图像的 3D 体积表示进行质量评估

• 批准号: 485010-2015
• 负责人: Clausi, David
• 金额: $ 1.82万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=584651
• 关键词: Quality; assessment; 3D; volume; representation

This project will aim at development and implementation of solutions for post-processing and quantitative analysis for digital pathology images to provide the pathologist with a digital simulated version of manual focusing with a microscope. Improvements in the reliability of scans and enhancing diagnostic quality help to develop fully automated diagnostic systems at a relatively low cost. The post-processing procedure involves visual representation of 3D images obtained from a stack of 2D pathology images. Challenges regarding in-focus and out-of-focus information, quantitative measurement of image quality, registration and fusion of images in a volume, and computational speed have to be addressed in this project.

该项目旨在开发和实施数字病理学图像的后处理和定量分析解决方案，为病理学家提供显微镜手动聚焦的数字模拟版本。提高扫描的可靠性和提高诊断质量有助于以相对较低的成本开发全自动诊断系统。后处理过程涉及从2D病理学图像的堆叠获得的3D图像的视觉表示。关于焦点和焦点外的信息，图像质量的定量测量，注册和融合的图像在体积，和计算速度的挑战必须在这个项目中得到解决。