no code implementations • 12 Mar 2024 • Ivo M. Baltruschat, Parvaneh Janbakhshi, Matthias Lenga
This work addresses the Brain Magnetic Resonance Image Synthesis for Tumor Segmentation (BraSyn) challenge, which was hosted as part of the Brain Tumor Segmentation (BraTS) challenge in 2023.
no code implementations • 20 Nov 2023 • Ivo M. Baltruschat, Parvaneh Janbakhshi, Melanie Dohmen, Matthias Lenga
In recent years, deep learning has been applied to a wide range of medical imaging and image processing tasks.
1 code implementation • 28 Mar 2023 • Ivo M. Baltruschat, Felix Kreis, Alexander Hoelscher, Melanie Dohmen, Matthias Lenga
Generative adversarial networks (GANs) have shown remarkable success in generating realistic images and are increasingly used in medical imaging for image-to-image translation tasks.
no code implementations • 23 Jan 2020 • Ivo M. Baltruschat, Leonhard Steinmeister, Hannes Nickisch, Axel Saalbach, Michael Grass, Gerhard Adam, Tobias Knopp, Harald Ittrich
Our simulations demonstrate that smart worklist prioritization by AI can reduce the average RTAT for critical findings in CXRs while maintaining a small maximum RTAT as FIFO.
no code implementations • 17 Oct 2018 • Ivo M. Baltruschat, Leonhard Steinmeister, Harald Ittrich, Gerhard Adam, Hannes Nickisch, Axel Saalbach, Jens von Berg, Michael Grass, Tobias Knopp
Chest radiography is the most common clinical examination type.
no code implementations • 6 Mar 2018 • Ivo M. Baltruschat, Hannes Nickisch, Michael Grass, Tobias Knopp, Axel Saalbach
The increased availability of X-ray image archives (e. g. the ChestX-ray14 dataset from the NIH Clinical Center) has triggered a growing interest in deep learning techniques.