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pro vyhledávání: '"Guendel, Sebastian"'
Robust and reliable anonymization of chest radiographs constitutes an essential step before publishing large datasets of such for research purposes. The conventional anonymization process is carried out by obscuring personal information in the images
Externí odkaz:
http://arxiv.org/abs/2209.11531
Autor:
Gündel, Sebastian, Setio, Arnaud A. A., Ghesu, Florin C., Grbic, Sasa, Georgescu, Bogdan, Maier, Andreas, Comaniciu, Dorin
Chest radiography is the most common radiographic examination performed in daily clinical practice for the detection of various heart and lung abnormalities. The large amount of data to be read and reported, with more than 100 studies per day for a s
Externí odkaz:
http://arxiv.org/abs/2104.05261
Autor:
Packhäuser, Kai, Gündel, Sebastian, Münster, Nicolas, Syben, Christopher, Christlein, Vincent, Maier, Andreas
Publikováno v:
Scientific Reports, 12, Article number: 14851 (2022)
With the rise and ever-increasing potential of deep learning techniques in recent years, publicly available medical datasets became a key factor to enable reproducible development of diagnostic algorithms in the medical domain. Medical data contains
Externí odkaz:
http://arxiv.org/abs/2103.08562
Autor:
Guendel, Sebastian, Setio, Arnaud Arindra Adiyoso, Grbic, Sasa, Maier, Andreas, Comaniciu, Dorin
Chest X-ray (CXR) is the most common examination for fast detection of pulmonary abnormalities. Recently, automated algorithms have been developed to classify multiple diseases and abnormalities in CXR scans. However, because of the limited availabil
Externí odkaz:
http://arxiv.org/abs/2008.02030
Autor:
Guendel, Sebastian, Maier, Andreas
The current accessibility to large medical datasets for training convolutional neural networks is tremendously high. The associated dataset labels are always considered to be the real "ground truth". However, the labeling procedures often seem to be
Externí odkaz:
http://arxiv.org/abs/1912.01966
Autor:
Ghesu, Florin C., Georgescu, Bogdan, Gibson, Eli, Guendel, Sebastian, Kalra, Mannudeep K., Singh, Ramandeep, Digumarthy, Subba R., Grbic, Sasa, Comaniciu, Dorin
The interpretation of chest radiographs is an essential task for the detection of thoracic diseases and abnormalities. However, it is a challenging problem with high inter-rater variability and inherent ambiguity due to inconclusive evidence in the d
Externí odkaz:
http://arxiv.org/abs/1906.07775
Autor:
Guendel, Sebastian, Ghesu, Florin C., Grbic, Sasa, Gibson, Eli, Georgescu, Bogdan, Maier, Andreas, Comaniciu, Dorin
Chest X-ray (CXR) is the most common X-ray examination performed in daily clinical practice for the diagnosis of various heart and lung abnormalities. The large amount of data to be read and reported, with 100+ studies per day for a single radiologis
Externí odkaz:
http://arxiv.org/abs/1905.06362
Autor:
Guendel, Sebastian, Grbic, Sasa, Georgescu, Bogdan, Zhou, Kevin, Ritschl, Ludwig, Meier, Andreas, Comaniciu, Dorin
Chest X-ray is the most common medical imaging exam used to assess multiple pathologies. Automated algorithms and tools have the potential to support the reading workflow, improve efficiency, and reduce reading errors. With the availability of large
Externí odkaz:
http://arxiv.org/abs/1803.04565
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