IRMtools: Software tools for Infrared and Raman Microscopy

IRMtools：红外和拉曼显微镜软件工具

• 批准号: 391069053
• 负责人: Professor Dr. Axel Mosig
• 金额: --
• 依托单位: Lehrstuhl für Informations- und Technikmanagement (IMTM)
• 依托单位国家: 德国
• 项目类别: Research data and software (Scientific Library Services and Information Systems)
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/391069053?language=en
• 关键词: IRMtools; Software; tools; Infrared; Raman

Infrared and Raman microscopy provide label-free approaches to characterize biological and histopathological samples at high spatial resolution and with great biochemical detail. Interpreting Infrared and Raman microscopic images involves substantial amount of computation, ranging from preprocessing of the pixel spectra of an image to different approaches from image processing and supervised or unsupervised machine learning. A remarkably large body of literature dealing with computational approaches for processing infrared and Raman microscopic images has been established in recent years.However, there are two remarkable software related gaps in the research field dealing with infrared Raman microscopy. First, the community lacks an open software platform where the proposed approaches can be assessed, compared and integrated into data analysis workflows. Second, the community lacks software with graphical user interfaces that makes the technology accessible to end users without specific computational or spectroscopic expertise. These software related gaps limit accessibility of the technology, in particular for applications in histopathology, where it could be demonstrated recently in a number of clinical studies that these label-free microscopy approaches promise higher precision for identifying subtypes of cancer than conventional histopathology.Our proposed research aims to overcome these two software related hurdles, and builds on a substantial set of software tools that have been developed within the PURE biomarker consortium in Bochum over the last six years. These software tools cover the complete range of functions required for applying infrared and Raman microscopy in histopathology and other applications, and have been practice-proven in several clinical studies conducted within the PURE consortium. These existing software packages prvoide the foundation to overcome the two software related gaps of the research community. Specifically, we will establish an open source software architecture around these tools, and equip them with easy-to-use graphical user interfaces for end users.The proposed development is embedded in an institutional network around the PURE consortium and the international CLIRSPEC network, as well as links to the proteomics hub of the German De.NBI bioinformatics network.

红外和拉曼显微镜提供了无标记的方法来表征生物和组织病理学样品在高空间分辨率和伟大的生化细节。解释红外和拉曼显微图像涉及大量的计算，从图像的像素光谱的预处理到图像处理和监督或无监督机器学习的不同方法。近几年来，有关红外和拉曼显微图像处理的计算机方法的文献已经相当多，但在红外拉曼显微图像处理的研究领域中，还存在两个与软件相关的空白。首先，社区缺乏一个开放的软件平台，可以评估，比较和集成到数据分析工作流程中的拟议方法。第二，社区缺乏具有图形用户界面的软件，使得没有特定计算或光谱专业知识的最终用户可以访问该技术。这些与软件相关的差距限制了该技术的可及性，特别是在组织病理学中的应用，最近在许多临床研究中可以证明，这些无标记显微镜方法比传统的组织病理学更能准确地识别癌症亚型。我们提出的研究旨在克服这两个与软件相关的障碍，并建立在过去六年来在波鸿的PURE生物标志物联盟内开发的大量软件工具的基础上。这些软件工具涵盖了在组织病理学和其他应用中应用红外和拉曼显微镜所需的全部功能，并已在PURE联盟内进行的几项临床研究中得到实践证明。这些现有的软件包提供了基础，以克服两个软件相关的研究社区的差距。具体来说，我们将围绕这些工具建立一个开源软件架构，并为最终用户配备易于使用的图形用户界面。拟议的开发嵌入在围绕PURE联盟和国际CLIRSPEC网络的机构网络中，以及与德国De.NBI生物信息学网络的蛋白质组学中心的链接。