5 Einträge gefunden

1. Automatic segmentation of the thalamus using a massively trained 3D convolutional neural network: higher sensitivity for the detection of reduced thalamus volume by improved inter-scanner stability

   1. Opfer, Roland
   2. Krüger, Julia
   3. Spies, Lothar
   4. Ostwaldt, Ann-Christin
   5. Kitzler, Hagen H.
   6. Schippling, Sven
   7. Buchert, Ralph

   2023 - Forschungsinformationssystem des UKE - frei zugänglich
2. 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
3. Single-subject analysis of regional brain volumetric measures can be strongly influenced by the method for head size adjustment

   1. Opfer, Roland
   2. Krüger, Julia
   3. Spies, Lothar
   4. Kitzler, Hagen H.
   5. Schippling, Sven
   6. Buchert, Ralph

   2022 - Forschungsinformationssystem des UKE - frei zugänglich
4. 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
5. 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