Machine learning based analysis of stroke lesions on mouse tissue sections.

An unbiased, automated and reliable method for analysis of brain lesions in tissue after ischemic stroke is missing. Manual infarct volumetry or by threshold-based semi-automated approaches is laborious, and biased to human error or biased by many false -positive and -negative data, respectively. Thereby, we developed a novel machine learning, atlas-based method for fully automated stroke analysis in mouse brain slices stained with 2% Triphenyltetrazolium-chloride (2% TTC), named "StrokeAnalyst", which runs on a user-friendly graphical interface.

Translational Block in Stroke: A Constructive and "Out-of-the-Box" Reappraisal.

Why can we still not translate preclinical research to clinical treatments for acute strokes? Despite > 1000 successful preclinical studies, drugs, and concepts for acute stroke, only two have reached clinical translation. This is the translational block. Yet, we continue to routinely model strokes using almost the same concepts we have used for over 30 years.