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Robust Automatic Threshold Selection (RATS) is a fast and noise robust
automatic thresholding method based on gradients in the image. The basic idea is to choose
the threshold at the intensity where the gradient are the highest.

When an image is mostly composed of background pixels, most of the automatic
thresholding methods are failing to produce a relevant threshold. This is mainly
caused because one mode is over represented compared to the other in the histogram
of the image. [...]

Unsupervised Segmentation for Myofiber Counting in Immunofluorescent Microscopy Images
Published in The Insight Journal
Published in The Insight Journal
The gold standard for measuring muscle regeneration in muscular dystrophy therapies is counting the number of dystrophin-positive muscle fibers on a cryostat muscle section immunostained for dystrophin. The standard process of manually counting a few thousand [...]
