4 Einträge gefunden

1. 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
2. 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
3. Automatic classification of dopamine transporter SPECT: deep convolutional neural networks can be trained to be robust with respect to variable image characteristics

   1. Wenzel, Markus
   2. Milletari, Fausto
   3. Krüger, Julia
   4. Lange, Catharina
   5. Schenk, Michael
   6. Apostolova, Ivayla
   7. Klutmann, Susanne

   2019 - Forschungsinformationssystem des UKE
4. Deep Learning in der SPECT und PET des Gehirns

   1. Buchert, Ralph
   2. Krüger, Julia
   3. Gessert, Nils Thorben
   4. Lehnert, Wencke
   5. Apostolova, Ivayla
   6. Klutmann, Susanne
   7. Schlaefer, Alexander

   2019 - TUHH Open Research