“Tonga”: A Novel Toolbox for Straightforward Bioimage Analysis - Ritchie, Alexandra; Laitinen, Suvi; Katajisto, Pekka; Englund, Johanna I. (Frontiers in Computer Science, 2022)
Techniques to acquire and analyze biological images are central to various life science fields. Imaging and downstream workflow can be complex and involve use of several tools, leading to creation of very specialized scripts and pipelines that are difficult to reproduce by other users. Although there are different commercial and open-source software available, non-expert users are often challenged by a knowledge gap in setting up analysis pipelines and selecting correct tools for extracting data from images. Moreover, a significant share of everyday image analysis requires simple tools, such as precise segmentation, cell counting and recording of fluorescent intensities. Hence, there is a clear need for platforms that are user-friendly, do not require extensive prior knowledge on bioimage analysis or coding, and perform everyday image analysis precisely. We set out to create a bioimage analysis software that would have a straightforward and user-friendly interface. The new software contains a toolbox that covers methods for common analysis tasks, including object segmentation and analysis, in a practical, reproducible, and modular fashion. Finally, the novel segmentation technique of the software is based on pairing of concave points that we show to work accurately across different cell types. Taken together, we have created a novel bioimage analysis toolbox that is easy to access and use. We envision our software being useful in several different circumstances ranging from analysis of cell cultures and histological sections to high-content data.