no code implementations • 2 Apr 2024 • Zdravko Marinov, Moon Kim, Jens Kleesiek, Rainer Stiefelhagen
In an initial user study involving four annotators, we assess existing robot users using our proposed metrics and find that robot users significantly deviate in performance and annotation behavior compared to real annotators.
1 code implementation • 24 Nov 2023 • Matthias Hadlich, Zdravko Marinov, Moon Kim, Enrico Nasca, Jens Kleesiek, Rainer Stiefelhagen
Deep learning has revolutionized the accurate segmentation of diseases in medical imaging.
no code implementations • 29 Sep 2023 • Mariana Lindo, Ana Sofia Santos, André Ferreira, Jianning Li, Gijs Luijten, Gustavo Correia, Moon Kim, Benedikt Michael Schaarschmidt, Cornelius Deuschl, Johannes Haubold, Jens Kleesiek, Jan Egger, Victor Alves
In this study, the generation of radiology impressions in different languages was automated by fine-tuning a model, publicly available, based on a multilingual text-to-text Transformer to summarize findings available in English, Portuguese, and German radiology reports.
1 code implementation • 30 Jun 2023 • Frederic Jonske, Moon Kim, Enrico Nasca, Janis Evers, Johannes Haubold, René Hosch, Felix Nensa, Michael Kamp, Constantin Seibold, Jan Egger, Jens Kleesiek
It is an open secret that ImageNet is treated as the panacea of pretraining.
1 code implementation • 6 Jun 2023 • Constantin Seibold, Alexander Jaus, Matthias A. Fink, Moon Kim, Simon Reiß, Ken Herrmann, Jens Kleesiek, Rainer Stiefelhagen
Results: Our resulting segmentation models demonstrated remarkable performance on CXR, with a high average model-annotator agreement between two radiologists with mIoU scores of 0. 93 and 0. 85 for frontal and lateral anatomy, while inter-annotator agreement remained at 0. 95 and 0. 83 mIoU.
1 code implementation • 24 Jan 2023 • Verena Jasmin Hallitschke, Tobias Schlumberger, Philipp Kataliakos, Zdravko Marinov, Moon Kim, Lars Heiliger, Constantin Seibold, Jens Kleesiek, Rainer Stiefelhagen
Recently, deep learning enabled the accurate segmentation of various diseases in medical imaging.