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ORCIDSebastian Gündel
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2020 – today
- 2024
[c8]Kai Packhäuser, Sebastian Gündel, Florian Thamm, Felix Denzinger, Andreas K. Maier:
Abstract: Utility-preserving Measure for Patient Privacy - Deep Learning-based Anonymization of Chest Radiographs. Bildverarbeitung für die Medizin 2024: 363- 2023
- [b1]Sebastian Gündel:
Recognition of Similarities and Abnormalities in Chest Radiographs (Erkennung von Ähnlichkeiten und Abnormalitäten in Thoraxröntgenbildern). University of Erlangen-Nuremberg, Germany, 2023 - [c7]Kai Packhäuser, Sebastian Gündel, Nicolas Münster, Christopher Syben, Vincent Christlein, Andreas K. Maier:
Abstract: Is Medical Chest X-ray Data Anonymous? - Deep Learning-based Patient Re-identification is Able to Exploit the Biometric Nature of Medical Chest X-ray Data. Bildverarbeitung für die Medizin 2023: 204 - [c6]Kai Packhäuser, Sebastian Gündel, Florian Thamm, Felix Denzinger, Andreas K. Maier:
Deep Learning-Based Anonymization of Chest Radiographs: A Utility-Preserving Measure for Patient Privacy. MICCAI (3) 2023: 262-272 - 2022
- [i8]Kai Packhäuser, Sebastian Gündel, Florian Thamm, Felix Denzinger, Andreas K. Maier:
Deep Learning-based Anonymization of Chest Radiographs: A Utility-preserving Measure for Patient Privacy. CoRR abs/2209.11531 (2022) - 2021
- [j1]Sebastian Gündel
, Arnaud A. A. Setio, Florin C. Ghesu, Sasa Grbic, Bogdan Georgescu, Andreas K. Maier, Dorin Comaniciu:
Robust classification from noisy labels: Integrating additional knowledge for chest radiography abnormality assessment. Medical Image Anal. 72: 102087 (2021) - [c5]Sebastian Gündel, Arnaud A. A. Setio, Sasa Grbic, Andreas Maier, Dorin Comaniciu:
Abstract: Extracting and Leveraging Nodule Features with Lung Inpainting for Local Feature Augmentation. Bildverarbeitung für die Medizin 2021: 288 - [i7]Kai Packhäuser, Sebastian Gündel, Nicolas Münster, Christopher Syben, Vincent Christlein, Andreas Maier:
Is Medical Chest X-ray Data Anonymous? CoRR abs/2103.08562 (2021) - [i6]Sebastian Gündel, Arnaud A. A. Setio, Florin C. Ghesu, Sasa Grbic, Bogdan Georgescu, Andreas Maier, Dorin Comaniciu:
Robust Classification from Noisy Labels: Integrating Additional Knowledge for Chest Radiography Abnormality Assessment. CoRR abs/2104.05261 (2021) - 2020
- [c4]Sebastian Gündel, Andreas K. Maier:
Epoch-Wise Label Attacks for Robustness Against Label Noise. Bildverarbeitung für die Medizin 2020: 287-292 - [c3]Sebastian Gündel, Arnaud A. A. Setio, Sasa Grbic, Andreas K. Maier, Dorin Comaniciu:
Extracting and Leveraging Nodule Features with Lung Inpainting for Local Feature Augmentation. MLMI@MICCAI 2020: 504-512 - [i5]Sebastian Gündel, Arnaud Arindra Adiyoso Setio, Sasa Grbic, Andreas Maier, Dorin Comaniciu:
Extracting and Leveraging Nodule Features with Lung Inpainting for Local Feature Augmentation. CoRR abs/2008.02030 (2020)
2010 – 2019
- 2019
- [c2]Florin C. Ghesu, Bogdan Georgescu, Eli Gibson, Sebastian Gündel, Mannudeep K. Kalra, Ramandeep Singh, Subba R. Digumarthy, Sasa Grbic, Dorin Comaniciu:
Quantifying and Leveraging Classification Uncertainty for Chest Radiograph Assessment. MICCAI (6) 2019: 676-684 - [i4]Sebastian Gündel, Florin C. Ghesu, Sasa Grbic, Eli Gibson, Bogdan Georgescu, Andreas K. Maier, Dorin Comaniciu:
Multi-task Learning for Chest X-ray Abnormality Classification on Noisy Labels. CoRR abs/1905.06362 (2019) - [i3]Florin C. Ghesu, Bogdan Georgescu, Eli Gibson, Sebastian Gündel, Mannudeep K. Kalra, Ramandeep Singh, Subba R. Digumarthy, Sasa Grbic, Dorin Comaniciu:
Quantifying and Leveraging Classification Uncertainty for Chest Radiograph Assessment. CoRR abs/1906.07775 (2019) - [i2]Sebastian Gündel, Andreas K. Maier:
Epoch-wise label attacks for robustness against label noise. CoRR abs/1912.01966 (2019) - 2018
- [c1]Sebastian Gündel, Sasa Grbic, Bogdan Georgescu, Siqi Liu, Andreas Maier, Dorin Comaniciu:
Learning to Recognize Abnormalities in Chest X-Rays with Location-Aware Dense Networks. CIARP 2018: 757-765 - [i1]Sebastian Gündel, Sasa Grbic, Bogdan Georgescu, Shaohua Kevin Zhou, Ludwig Ritschl, Andreas Meier, Dorin Comaniciu:
Learning to recognize Abnormalities in Chest X-Rays with Location-Aware Dense Networks. CoRR abs/1803.04565 (2018)
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