A guide to accurate reporting in digital image processing – can anyone reproduce your quantitative analysis?
Author(s) -
Jesse Aaron,
TengLeong Chew
Publication year - 2021
Publication title -
journal of cell science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.384
H-Index - 278
eISSN - 1477-9137
pISSN - 0021-9533
DOI - 10.1242/jcs.254151
Subject(s) - workflow , documentation , digital image analysis , image processing , data science , biology , variety (cybernetics) , reproducibility , image (mathematics) , computer science , artificial intelligence , computer vision , database , statistics , mathematics , programming language
Considerable attention has been recently paid to improving replicability and reproducibility in life science research. This has resulted in commendable efforts to standardize a variety of reagents, assays, cell lines and other resources. However, given that microscopy is a dominant tool for biologists, comparatively little discussion has been offered regarding how the proper reporting and documentation of microscopy relevant details should be handled. Image processing is a critical step of almost any microscopy-based experiment; however, improper, or incomplete reporting of its use in the literature is pervasive. The chosen details of an image processing workflow can dramatically determine the outcome of subsequent analyses, and indeed, the overall conclusions of a study. This Review aims to illustrate how proper reporting of image processing methodology improves scientific reproducibility and strengthens the biological conclusions derived from the results.
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