TissueGnostics (TG) provides streamlined solutions for both biomedical imaging and image analysis. The goal of TG is to bring the same type of phenotypical analysis of single cells from Flow Cytometry into tissue context. The merging of image analysis software and high-quality optics and robotics has allowed TG to create the TissueFAXS system - a fully automated system which can scan slides/well plates and automatically quantify marker expression per cell. Going a step beyond that is StrataQuest - a software development platform for creating complex image analysis algorithms that can automatically detect multicellular structures within scanned tissue sections for a highly detailed contextual tissue analysis.
The imaging systems are modular and upgradable. Every system can be customized to offer the following capabilities: brightfield scanning, widefield fluorescence, confocal, and multispectral. Every system can come either in an upright configuration for scanning slides only, or inverted for scanning well plates and slides. Each TissueFAXS system comes with either an 8-slide stage, or a high-throughput automatic 120 slide loading system only available for the upright TissueFAXS system configuration. TissueFAXS systems can come with high powered LED light engines combined with multi bandpass filter cubes for high speed fluorescence scanning.
Image analysis software comes in 3 forms: TissueQuest for fluorescence image analysis, HistoQuest for brightfield image analysis, and StrataQuest for multicellular contextual tissue analysis for both brightfield and fluorescence images. TissueQuest and HistoQuest are streamlined for rapidly acquiring nuclear segmentation and marker quantification per cell. StrataQuest offers much more in terms of image analysis and is therefore more complex, which is why TissueGnostics offers the development of customized algorithms as a service to researchers. Every StrataQuest solution (or APP) includes a simplified user interface that is made by the underlying algorithm, and contains macros so that even researchers with little or no experience in image analysis can obtain high quality data from analysing their scanned images.