Bridging imaging users to imaging analysis – A community survey

Author:

Sivagurunathan Suganya1ORCID,Marcotti Stefania2ORCID,Nelson Carl J34ORCID,Jones Martin L5ORCID,Barry David J6ORCID,Slater Thomas J A7ORCID,Eliceiri Kevin W8ORCID,Cimini Beth A1ORCID

Affiliation:

1. Imaging Platform Broad Institute of MIT and Harvard Cambridge Massachusetts USA

2. Randall Centre for Cell and Molecular Biophysics and Research Management & Innovation Directorate King's College London London UK

3. School of Physics and Astronomy University of Glasgow Glasgow UK

4. Current affiliation: Fjelltopp Ltd Lancashire UK

5. Electron Microscopy Science Technology Platform Francis Crick Institute London UK

6. Advanced Light Microscopy Science Technology Platform Francis Crick Institute London UK

7. School of Chemistry Cardiff University Cardiff UK

8. Center for Quantitative Cell Imaging University of Wisconsin‐Madison Madison Wisconsin United States

Abstract

AbstractThe ‘Bridging Imaging Users to Imaging Analysis’ survey was conducted in 2022 by the Center for Open Bioimage Analysis (COBA), BioImaging North America (BINA) and the Royal Microscopical Society Data Analysis in Imaging Section (RMS DAIM) to understand the needs of the imaging community. Through multichoice and open‐ended questions, the survey inquired about demographics, image analysis experiences, future needs and suggestions on the role of tool developers and users. Participants of the survey were from diverse roles and domains of the life and physical sciences. To our knowledge, this is the first attempt to survey cross‐community to bridge knowledge gaps between physical and life sciences imaging. Survey results indicate that respondents' overarching needs are documentation, detailed tutorials on the usage of image analysis tools, user‐friendly intuitive software, and better solutions for segmentation, ideally in a format tailored to their specific use cases. The tool creators suggested the users familiarise themselves with the fundamentals of image analysis, provide constant feedback and report the issues faced during image analysis while the users would like more documentation and an emphasis on tool friendliness. Regardless of the computational experience, there is a strong preference for ‘written tutorials’ to acquire knowledge on image analysis. We also observed that the interest in having ‘office hours’ to get an expert opinion on their image analysis methods has increased over the years. The results also showed less‐than‐expected usage of online discussion forums in the imaging community for solving image analysis problems. Surprisingly, we also observed a decreased interest among the survey respondents in deep/machine learning despite the increasing adoption of artificial intelligence in biology. In addition, the community suggests the need for a common repository for the available image analysis tools and their applications. The opinions and suggestions of the community, released here in full, will help the image analysis tool creation and education communities to design and deliver the resources accordingly.

Funder

National Institute of General Medical Sciences

Cancer Research UK

Wellcome Trust

Biotechnology and Biological Sciences Research Council

Publisher

Wiley

Subject

Histology,Pathology and Forensic Medicine

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