no code implementations • 4 Oct 2023 • Ayhan Can Erdur, Daniel Scholz, Josef A. Buchner, Stephanie E. Combs, Daniel Rueckert, Jan C. Peeken
Our experiments demonstrate the utility of the ad ditional blob loss and the subtraction sequence.
no code implementations • 1 Mar 2022 • Fernando Navarro, Guido Sasahara, Suprosanna Shit, Ivan Ezhov, Jan C. Peeken, Stephanie E. Combs, Bjoern H. Menze
Automatic localization and segmentation of organs-at-risk (OAR) in CT are essential pre-processing steps in medical image analysis tasks, such as radiation therapy planning.
no code implementations • 14 May 2021 • Fernando Navarro, Christopher Watanabe, Suprosanna Shit, Anjany Sekuboyina, Jan C. Peeken, Stephanie E. Combs, Bjoern H. Menze
Self-supervision has demonstrated to be an effective learning strategy when training target tasks on small annotated data-sets.
no code implementations • 17 Nov 2020 • Daniel M. Lang, Jan C. Peeken, Stephanie E. Combs, Jan J. Wilkens, Stefan Bartzsch
We investigated the ability of deep learning models for imaging based HPV status detection.
no code implementations • MIDL 2019 • Fernando Navarro, Anjany Sekuboyina, Diana Waldmannstetter, Jan C. Peeken, Stephanie E. Combs, Bjoern H. Menze
Robust localization of organs in computed tomography scans is a constant pre-processing requirement for organ-specific image retrieval, radiotherapy planning, and interventional image analysis.