IRMtools: Software tools for Infrared and Raman Microscopy

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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.