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Frederic Madesta
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2020 – today
- 2022
- [c7]Samuel Schüttler, Frederic Madesta, Thomas Rösch, René Werner, Rüdiger Schmitz:
Reinforcement learning-basierte Patchpriorisierung zur beschleunigten Segmentierung von hochauflösenden Endoskopievideodaten. Bildverarbeitung für die Medizin 2022: 339-344 - [i4]Frederic Madesta, Thilo Sentker, Tobias Gauer, René Werner:
Deep learning-based conditional inpainting for restoration of artifact-affected 4D CT images. CoRR abs/2203.06431 (2022) - 2021
- [j2]Rüdiger Schmitz, Frederic Madesta
, Maximilian Nielsen
Multi-scale fully convolutional neural networks for histopathology image segmentation: From nuclear aberrations to the global tissue architecture. Medical Image Anal. 70: 101996 (2021) - [c6]Frederic Madesta, Rüdiger Schmitz, Thomas Rösch, René Werner:
Abstract: Widening the Focus - Biomedical Image Segmentation Challenges and the Underestimated Role of Patch Sampling and Inference Strategies. Bildverarbeitung für die Medizin 2021: 253 - 2020
- [j1]Nils Gessert
Skin Lesion Classification Using CNNs With Patch-Based Attention and Diagnosis-Guided Loss Weighting. IEEE Trans. Biomed. Eng. 67(2): 495-503 (2020) - [c5]Frederic Madesta
Widening the Focus: Biomedical Image Segmentation Challenges and the Underestimated Role of Patch Sampling and Inference Strategies. MICCAI (4) 2020: 289-298
2010 – 2019
- 2019
- [c4]Thilo Sentker
Patient-specific 4D Monte Carlo dose accumulation using correspondence-model-based motion prediction. Medical Imaging: Image-Guided Procedures 2019: 1095109 - [c3]Frederic Madesta, Tobias Gauer, Thilo Sentker
Self-consistent deep learning-based boosting of 4D cone-beam computed tomography reconstruction. Medical Imaging: Image Processing 2019: 1094902 - [i3]Nils Gessert, Thilo Sentker, Frederic Madesta, Rüdiger Schmitz, Helge Kniep, Ivo M. Baltruschat, René Werner, Alexander Schlaefer:
Skin Lesion Classification Using CNNs with Patch-Based Attention and Diagnosis-Guided Loss Weighting. CoRR abs/1905.02793 (2019) - [i2]Rüdiger Schmitz, Frederic Madesta, Maximilian Nielsen, René Werner, Thomas Rösch:
Multi-scale fully convolutional neural networks for histopathology image segmentation: from nuclear aberrations to the global tissue architecture. CoRR abs/1909.10726 (2019) - 2018
- [c2]Lasse Böhme, Frederic Madesta, Thilo Sentker
Combining Good Old Random Forest and DeepLabv3+ for ISLES 2018 CT-Based Stroke Segmentation. BrainLes@MICCAI (1) 2018: 335-342 - [c1]Thilo Sentker
GDL-FIRE ^\text 4D : Deep Learning-Based Fast 4D CT Image Registration. MICCAI (1) 2018: 765-773 - [i1]Nils Gessert
Skin Lesion Diagnosis using Ensembles, Unscaled Multi-Crop Evaluation and Loss Weighting. CoRR abs/1808.01694 (2018)
Coauthor Index
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