5 Einträge gefunden

1. Infratentorial lesions in multiple sclerosis patients: intra- and inter-rater variability in comparison to a fully automated segmentation using 3D convolutional neural networks

   1. Krüger, Julia
   2. Ostwaldt, Ann-Christin
   3. Spies, Lothar
   4. Geisler, Benjamin
   5. Schlaefer, Alexander
   6. Kitzler, Hagen H.
   7. Schippling, Sven

   2022 - TUHH Open Research
2. Fully automated longitudinal segmentation of new or enlarged multiple sclerosis lesions using 3D convolutional neural networks

   1. Krüger, Julia
   2. Opfer, Roland
   3. Gessert, Nils Thorben
   4. Ostwaldt, Ann-Christin
   5. Manogaran, Paraveena
   6. Kitzler, Hagen H.
   7. Schlaefer, Alexander

   2020 - TUHH Open Research - frei zugänglich
3. Multiple sclerosis lesion activity segmentation with attention-guided two-path CNNs

   1. Gessert, Nils Thorben
   2. Krüger, Julia
   3. Opfer, Roland
   4. Ostwaldt, Ann-Christin
   5. Manogaran, Praveena
   6. Kitzler, Hagen H.
   7. Schippling, Sven

   2020 - TUHH Open Research
4. Fully automated lesion segmentation using heavily trained 3D convolutional neural networks are equivalent to manual expert segmentations

   1. Krüger, Julia
   2. Opfer, Roland
   3. Gessert, Nils Thorben
   4. Ostwaldt, Ann-Christin
   5. Walker-Egger, Christine
   6. Manogaran, Paraveena
   7. Wang, Chenyu

   2019 - TUHH Open Research
5. Fully automated longitudinal segmentation of new or enlarging multiple sclerosis (MS) lesions using 3D convolutional neural networks

   1. Krüger, Julia
   2. Opfer, Roland
   3. Gessert, Nils Thorben
   4. Schippling, Sven
   5. Ostwaldt, Ann-Christin
   6. Walker-Egger, Christine
   7. Manogaran, Paraveena

   2019 - TUHH Open Research