no code implementations • 7 Sep 2023 • Sophie Ostmeier, Brian Axelrod, Benjamin Pulli, Benjamin F. J. Verhaaren, Abdelkader Mahammedi, Yongkai Liu, Christian Federau, Greg Zaharchuk, Jeremy J. Heit
Conclusion: A model trained on random expert sampling can identify the presence and location of acute ischemic brain tissue on Non-Contrast CT similar to CT perfusion and with better consistency than experts.
no code implementations • 17 Jan 2021 • Christopher Vogelsanger, Christian Federau
Multiple Sclerosis (MS) and microvascular leukoencephalopathy are two distinct neurological conditions, the first caused by focal autoimmune inflammation in the central nervous system, the second caused by chronic white matter damage from atherosclerotic microvascular disease.
1 code implementation • 5 Oct 2020 • Moritz Platscher, Jonathan Zopes, Christian Federau
We demonstrate with the example of ischemic stroke that an improvement in lesion segmentation is feasible using deep learning based augmentation.
no code implementations • 11 Aug 2020 • Jonathan Zopes, Moritz Platscher, Silvio Paganucci, Christian Federau
The segmentation quality is quantified using the Dice metric for a total of 27 anatomical structures.
no code implementations • 24 Jun 2020 • Alejandro Ungría Hirte, Moritz Platscher, Thomas Joyce, Jeremy J. Heit, Eric Tranvinh, Christian Federau
We show that high quality, diverse and realistic-looking diffusion-weighted magnetic resonance images can be synthesized using deep generative models.