1 code implementation • 14 Aug 2019 • Fernando Navarro, Suprosanna Shit, Ivan Ezhov, Johannes Paetzold, Andrei Gafita, Jan Peeken, Stephanie Combs, Bjoern Menze
Multi-organ segmentation in whole-body computed tomography (CT) is a constant pre-processing step which finds its application in organ-specific image retrieval, radiotherapy planning, and interventional image analysis.
1 code implementation • MIDL 2019 • Ahmad B Qasim, Ivan Ezhov, Suprosanna Shit, Oliver Schoppe, Johannes Paetzold, Anjany Sekuboyina, Florian Kofler, Jana Lipkova, Hongwei Li, Bjoern Menze
Exploiting learning algorithms under scarce data regimes is a limitation and a reality of the medical imaging field.
no code implementations • 10 Mar 2021 • Florian Kofler, Ivan Ezhov, Fabian Isensee, Fabian Balsiger, Christoph Berger, Maximilian Koerner, Beatrice Demiray, Julia Rackerseder, Johannes Paetzold, Hongwei Li, Suprosanna Shit, Richard McKinley, Marie Piraud, Spyridon Bakas, Claus Zimmer, Nassir Navab, Jan Kirschke, Benedikt Wiestler, Bjoern Menze
It is often unclear how to optimize abstract metrics, such as human expert perception, in convolutional neural network (CNN) training.
no code implementations • 24 Oct 2021 • Giles Tetteh, Fernando Navarro, Johannes Paetzold, Jan Kirschke, Claus Zimmer, Bjoern H. Menze
First, it is time-consuming - the clinician needs to scan through several slices of images to ascertain the region of interest before deciding on what severity grade to assign to a patient.
1 code implementation • 7 Nov 2021 • Ivan Ezhov, Kevin Scibilia, Katharina Franitza, Felix Steinbauer, Suprosanna Shit, Lucas Zimmer, Jana Lipkova, Florian Kofler, Johannes Paetzold, Luca Canalini, Diana Waldmannstetter, Martin Menten, Marie Metz, Benedikt Wiestler, Bjoern Menze
Current treatment planning of patients diagnosed with a brain tumor, such as glioma, could significantly benefit by accessing the spatial distribution of tumor cell concentration.
1 code implementation • 19 Mar 2022 • Suprosanna Shit, Rajat Koner, Bastian Wittmann, Johannes Paetzold, Ivan Ezhov, Hongwei Li, Jiazhen Pan, Sahand Sharifzadeh, Georgios Kaissis, Volker Tresp, Bjoern Menze
We leverage direct set-based object prediction and incorporate the interaction among the objects to learn an object-relation representation jointly.
no code implementations • 17 May 2022 • Florian Kofler, Ivan Ezhov, Lucas Fidon, Izabela Horvath, Ezequiel de la Rosa, John LaMaster, Hongwei Li, Tom Finck, Suprosanna Shit, Johannes Paetzold, Spyridon Bakas, Marie Piraud, Jan Kirschke, Tom Vercauteren, Claus Zimmer, Benedikt Wiestler, Bjoern Menze
To approximate human quality ratings on scarce expert data, we train surrogate quality estimation models.
1 code implementation • 23 Aug 2022 • Felix Meissen, Johannes Paetzold, Georgios Kaissis, Daniel Rueckert
Most commonly, the anomaly detection model generates a "normal" version of an input image, and the pixel-wise $l^p$-difference of the two is used to localize anomalies.
no code implementations • 3 Dec 2022 • Hongwei Bran Li, Chinmay Prabhakar, Suprosanna Shit, Johannes Paetzold, Tamaz Amiranashvili, JianGuo Zhang, Daniel Rueckert, Juan Eugenio Iglesias, Benedikt Wiestler, Bjoern Menze
We find that in the natural image domain, CSR behaves on par with the supervised one on several perceptual tests as a metric, and in the medical domain, CSR better quantifies perceptual similarity concerning the experts' ratings.
no code implementations • 11 Jan 2024 • Barry Shichen Hu, Siyun Liang, Johannes Paetzold, Huy H. Nguyen, Isao Echizen, Jiapeng Tang
To avoid these limitations, we first unify the design choices in previous works and then propose a simplified Transformer-based model to extract richer and more robust geometric features for the surface normal estimation task.