28 citations · 47 across the 8 of their papers we have counts for
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cs.CV2023★ 12 cited
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…
cs.CV2020★ 5 cited
Diffusion-Weighted Magnetic Resonance Brain Images Generation with Generative Adversarial Networks and Variational Autoencoders: A Comparison Study
Alejandro Ungría Hirte, Moritz Platscher, Thomas Joyce +3
We show that high quality, diverse and realistic-looking diffusion-weighted magnetic resonance images can be synthesized using deep generative models. Based on professional neurora…