Portable and Adaptive Data Analysis Workflows for Real-Time 3D Vision (B02)

用于实时 3D 视觉的便携式自适应数据分析工作流程 (B02)

• 批准号: 444757230
• 金额: --
• 依托单位: Institut für Physik
• 依托单位国家: 德国
• 项目类别: Collaborative Research Centres
• 财政年份: 2020
• 资助国家: 德国
• 起止时间: 2019-12-31 至 2023-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/444757230?language=en
• 关键词: Portable; Adaptive; Data; Analysis; Workflows

In many Natural Sciences, microscopy is key to discover things that have never been seen or captured by cameras before. In high-end microscopy, resolution approaches the wavelength of the probing radiation, leading to images that are recorded with partially coherent, potentially unidirectional, or even polarized illumination plagued by various diffraction effects. The reconstruction algorithms processing such data are compute- and/or memory-intensive and are typically vendor-specific black-box algorithms, which are impossible to port and hard to modify or maintain. The aim of this interdiscipli-nary subproject is to develop a toolbox and platform for the flexible creation of vendor-agnostic DAWs for the near-real time analysis of microscopic images. It addresses portability across microscopes, dependability of analysis pipelines, and adaptation to different measurement types and available re-sources. Important cooperations will be established with B5 on estimating resource requirements and with B4 on optimizing network traffic. The subproject will be carried out by Prof. Eisert, an expert in online manipulation and analysis of video streams, and Prof. Koch, an expert in developing novel techniques in electron microscopy and optical microscopy.

在许多自然科学中，显微镜是发现以前从未被相机看到或捕捉到的事物的关键。在高端显微镜中，分辨率接近探测辐射的波长，导致图像记录与部分相干，潜在的单向，甚至偏光受到各种衍射效应的困扰。处理此类数据的重构算法是计算和/或内存密集型的，通常是特定于供应商的黑盒算法，不可能移植，也难以修改或维护。这个跨学科子项目的目标是开发一个工具箱和平台，用于灵活地创建与供应商无关的daw，用于近实时的微观图像分析。它解决了显微镜的可移植性，分析管道的可靠性，以及对不同测量类型和可用资源的适应。将与B5在估算资源需求方面建立重要合作，与B4在优化网络流量方面建立重要合作。该子项目将由在线操作和视频流分析专家Eisert教授和电子显微镜和光学显微镜新技术开发专家Koch教授共同负责。