Creating and troubleshooting microscopy analysis workflows: Common challenges and common solutions

Abstract

As microscopy diversifies and becomes ever more complex, the problem of quantification of microscopy images has emerged as a major roadblock for many researchers. All researchers must face certain challenges in turning microscopy images into answers, independent of their scientific question and the images they have generated. Challenges may arise at many stages throughout the analysis process, including handling of the image files, image pre‐processing, object finding, or measurement, and statistical analysis. While the exact solution required for each obstacle will be problem‐specific, by keeping analysis in mind, optimizing data quality, understanding tools and tradeoffs, breaking workflows and data sets into chunks, talking to experts, and thoroughly documenting what has been done, analysts at any experience level can learn to overcome these challenges and create better and easier image analyses.

A practical guide to bioimaging research data management in core facilities

“…[85][86][87][88] Image analysis is a science in itself, and aspects to consider are outlined elsewhere. [89][90][91][92][93][94] Notably, data management is crucial in image analysis: accessing large data sets, sharing copies of data or results, maintaining records of processed data and their provenance and associating results with the corresponding raw data for later exploration. 95 This becomes even more pivotal in the context of automated analysis pipelines, where the code heavily relies on well-structured data sources.…”