32 citations · 57 across the 3 of their papers we have counts for
3 papers
Random Expert Sampling for Deep Learning Segmentation of Acute Ischemic Stroke on Non-contrast CT
Sophie Ostmeier, Brian Axelrod, Benjamin Pulli +6
Purpose: Multi-expert deep learning training methods to automatically quantify ischemic brain tissue on Non-Contrast CT Materials and Methods: The data set consisted of 260 Non-Con…
Non-inferiority of Deep Learning Acute Ischemic Stroke Segmentation on Non-Contrast CT Compared to Expert Neuroradiologists
Sophie Ostmeier, Brian Axelrod, Benjamin F. J. Verhaaren +7
To determine if a convolutional neural network (CNN) deep learning model can accurately segment acute ischemic changes on non-contrast CT compared to neuroradiologists. Non-contras…
USE-Evaluator: Performance Metrics for Medical Image Segmentation Models with Uncertain, Small or Empty Reference Annotations
Sophie Ostmeier, Brian Axelrod, Jeroen Bertels +6
Performance metrics for medical image segmentation models are used to measure the agreement between the reference annotation and the predicted segmentation. Usually, overlap metric…