12 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. Capturing Inter-Slice Dependencies of 3D Brain MRI-Scans for Unsupervised Anomaly Detection

   1. Behrendt, Finn
   2. Bengs, Marcel
   3. Bhattacharya, Debayan
   4. Krüger, Julia
   5. Opfer, Roland
   6. Schlaefer, Alexander

   2022 - TUHH Open Research
3. Data-efficient vision transformers for multi-label sisease classification on chest radiographs

   1. Behrendt, Finn
   2. Bhattacharya, Debayan
   3. Krüger, Julia
   4. Opfer, Roland
   5. Schlaefer, Alexander

   2022 - TUHH Open Research - frei zugänglich
4. 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
5. Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age prediction

   1. Bengs, Marcel
   2. Behrendt, Finn
   3. Laves, Max-Heinrich
   4. Krüger, Julia
   5. Opfer, Roland
   6. Schlaefer, Alexander

   2022 - TUHH Open Research
6. 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
7. Unsupervised anomaly detection in 3D brain MRI using deep learning with impured training data

   1. Behrendt, Finn
   2. Bengs, Marcel
   3. Rogge, Frederik
   4. Krüger, Julia
   5. Opfer, Roland
   6. Schlaefer, Alexander

   2022 - TUHH Open Research
8. Three-dimensional deep learning with spatial erasing for unsupervised anomaly segmentation in brain MRI

   1. Bengs, Marcel
   2. Behrendt, Finn
   3. Krüger, Julia
   4. Opfer, Roland
   5. Schlaefer, Alexander

   2021 - TUHH Open Research - frei zugänglich
9. 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
10. 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
11. 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
12. Fully Automatic MRI-Based Hippocampus Volumetry Using FSL-FIRST: Intra-Scanner Test-Retest Stability, Inter-Field Strength Variability, and Performance as Enrichment Biomarker for Clinical Trials Using Prodromal Target Populations at Risk for Alzheimer's Disease

    1. Cavedo, Enrica
    2. Suppa, Per
    3. Lange, Catharina
    4. Opfer, Roland
    5. Lista, Simone
    6. Galluzzi, Samantha
    7. Schwarz, Adam J

    2017 - Forschungsinformationssystem des UKE