ABSTRACT
Running on the highly popular and accessible ImageJ/Fiji platform for biological image analysis, we have established AutoMorFi as a streamlined interface for automated whole-image morphometric analysis that generates at least 47 measurements per cell or object in under 1 minute. We performed multiple validated cluster and principal component analyses on nonredundant morphometric parameters derived from AutoMorFi for various cell types, objects, and organisms. We used images of rodent macrophages, human postmortem brain tissues from multiple sclerosis (MS) and Alzheimer’s disease (AD) patients, iPSC/animal models for Down’s syndrome and autism spectrum disorder (ASD), and organisms such as sea anemone and corals. AutoMorFi’s adaptability extends across diverse imaging modalities including brightfield, confocal, or widefield fluorescence microscopy as well as underwater photography. Due to its unlimited and unbiased sampling across any image and high potential for modification and customization, using AutoMorFi has led to the discovery of new distinguishing features in previously studied cell types and organisms as well as the development of rapid diagnostic approaches. AutoMorFi represents a transformative tool that will accelerate morphometric analysis and offer broad relevance in biological studies.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
The abstract, experiment related to Fig. 4c, and troubleshooting instructions in Supplementary Note 3 were updated. Supplementary Note 5 was added for AutoMorFi analysis of scaled color photographs. Supplementary Note 6 was added to provide an additional output matching app to collate all AutoMorFi results for individual cells. Supplementary Note 6 also refers to the uploaded Supplementary Software 1.
