no code implementations • 25 Oct 2023 • Christian Harder, Moritz Fuchs, Yuri Tolkach, Anirban Mukhopadhyay
We thoroughly evaluate the impact of the employed generative models on state-of-the-art neural networks in terms of accuracy, convergence speed and ensembling.
no code implementations • 30 Sep 2023 • Amin Ranem, Niklas Babendererde, Moritz Fuchs, Anirban Mukhopadhyay
Medical imaging plays a critical role in the diagnosis and treatment planning of various medical conditions, with radiology and pathology heavily reliant on precise image segmentation.
1 code implementation • 3 Aug 2023 • Yannik Frisch, Moritz Fuchs, Antoine Sanner, Felix Anton Ucar, Marius Frenzel, Joana Wasielica-Poslednik, Adrian Gericke, Felix Mathias Wagner, Thomas Dratsch, Anirban Mukhopadhyay
Motivated by this, we analyse cataract surgery video data for the worst-performing phases of a pre-trained downstream tool classifier.
1 code implementation • 29 Sep 2022 • Nicolas Wagner, Moritz Fuchs, Yuri Tolkach, Anirban Mukhopadhyay
As a solution, we propose BottleGAN, a generative model that can computationally align the staining styles of many laboratories and can be trained in a privacy-preserving manner to foster federated learning in computational pathology.
no code implementations • 5 Aug 2022 • Camila Gonzalez, Karol Gotkowski, Moritz Fuchs, Andreas Bucher, Armin Dadras, Ricarda Fischbach, Isabel Kaltenborn, Anirban Mukhopadhyay
Automatic segmentation of ground glass opacities and consolidations in chest computer tomography (CT) scans can potentially ease the burden of radiologists during times of high resource utilisation.
1 code implementation • 1 Aug 2022 • Jonathan Stieber, Moritz Fuchs, Anirban Mukhopadhyay
FrOoDo is an easy-to-use and flexible framework for Out-of-Distribution detection tasks in digital pathology.