8 Einträge gefunden

1. Unsupervised Anomaly Detection of Paranasal Anomalies in the Maxillary Sinus

   1. Bhattacharya, Debayan
   2. Behrendt, Finn
   3. Becker, Benjamin Tobias
   4. Beyersdorff, Dirk
   5. Petersen, Elina
   6. Petersen, Marvin
   7. Cheng, Bastian

   2023 - TUHH Open Research
2. Squeeze and multi-context attention for polyp segmentation

   1. Bhattacharya, Debayan
   2. Eggert, Dennis
   3. Betz, Christian Stephan
   4. Schlaefer, Alexander

   2022 - TUHH Open Research - frei zugänglich
3. Self-supervised U-Net for segmenting flat and sessile polyps

   1. Bhattacharya, Debayan
   2. Betz, Christian
   3. Eggert, Dennis
   4. Schlaefer, Alexander

   2022 - TUHH Open Research
4. In vivo detection of head and neck tumors by hyperspectral imaging combined with deep learning methods

   1. Eggert, Dennis
   2. Bengs, Marcel
   3. Westermann, Stephan
   4. Gessert, Nils Thorben
   5. Gerstner, Andreas
   6. Müller, Nina
   7. Bewarder, Julian

   2022 - TUHH Open Research - frei zugänglich
5. Self-supervised U-Net for segmenting flat and sessile polyps

   1. Bhattacharya, Debayan
   2. Betz, Christian Stephan
   3. Eggert, Dennis
   4. Schlaefer, Alexander

   2021 - TUHH Open Research
6. Dual Parallel Reverse Attention Edge Network : DPRA-EdgeNet

   1. Bhattacharya, Debayan
   2. Betz, Christian Stephan
   3. Eggert, Dennis
   4. Schlaefer, Alexander

   2021 - TUHH Open Research
7. Spectral-spatial Recurrent-Convolutional Networks for In-Vivo Hyperspectral Tumor Type Classification

   1. Bengs, Marcel
   2. Gessert, Nils Thorben
   3. Laffers, Wiebke
   4. Eggert, Dennis
   5. Westermann, Stephan
   6. Mueller, Nina A.
   7. Gerstner, Andreas O. H.

   2020 - TUHH Open Research
8. Spatio-spectral deep learning methods for in-vivo hyperspectral laryngeal cancer detection

   1. Bengs, Marcel
   2. Westermann, Stephan
   3. Gessert, Nils Thorben
   4. Eggert, Dennis
   5. Gerstner, Andreas O. H.
   6. Mueller, Nina A.
   7. Betz, Christian Stephan

   2020 - TUHH Open Research