A workflow for segmenting, counting, measuring and analysing microscopy images, disease images, particle images and tissue sections.
Standardise image names, formats, resolution and experimental groups, and keep a backup of the original images.
Never overwrite original images; save all processed results to a new folder.
Crop, calibrate scale, subtract background, split channels and check brightness and contrast.
Use the same preprocessing parameters for images from different groups.
Choose threshold segmentation, machine learning segmentation or object detection depending on the image type.
Spot-check segmentation results manually; don't simply trust the automatic output.
Export metrics such as area, count, length, grey value, fluorescence intensity or lesion proportion.
Keep image IDs and experimental groups in the exported table for statistical analysis.
Run statistical tests on image metrics and visualise them to produce results figures for the paper.
Mind sample independence: multiple objects in one image are not necessarily independent replicates.
