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Ischemic Stroke Lesion Segmentation challenge (ISLES 2022) offers a platformfor researchers to compare their solutions to 3D segmentation of ischemicstroke regions from 3D MRIs. In this work, we describe our solution to ISLES2022 segmentation task. We re-sample all images to a common resolution, use twoinput MRI modalities (DWI and ADC) and train SegResNet semantic segmentationnetwork from MONAI. The final submission is an ensemble of 15 models (from 3runs of 5-fold cross validation). Our solution (team name NVAUTO) achieves thetop place in terms of Dice metric (0.824), and overall rank 2 (based on thecombined metric ranking).

Automated ischemic stroke lesion segmentation from 3D MRI