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12 Einträge gefunden

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
2023 - Forschungsinformationssystem des UKE - frei zugänglich
Infratentorial lesions in multiple sclerosis patients: intra- and inter-rater variability in comparison to a fully automated segmentation using 3D convolutional neural networks
2022 - TUHH Open Research
Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age prediction
2022 - TUHH Open Research
Single-subject analysis of regional brain volumetric measures can be strongly influenced by the method for head size adjustment
2022 - Forschungsinformationssystem des UKE - frei zugänglich
Data-efficient vision transformers for multi-label sisease classification on chest radiographs
2022 - TUHH Open Research - frei zugänglich
Capturing Inter-Slice Dependencies of 3D Brain MRI-Scans for Unsupervised Anomaly Detection
2022 - TUHH Open Research
Unsupervised anomaly detection in 3D brain MRI using deep learning with impured training data
2022 - TUHH Open Research
Three-dimensional deep learning with spatial erasing for unsupervised anomaly segmentation in brain MRI
2021 - TUHH Open Research - frei zugänglich
Multiple sclerosis lesion activity segmentation with attention-guided two-path CNNs
2020 - TUHH Open Research
Fully automated longitudinal segmentation of new or enlarged multiple sclerosis lesions using 3D convolutional neural networks
2020 - TUHH Open Research - frei zugänglich
Fully automated lesion segmentation using heavily trained 3D convolutional neural networks are equivalent to manual expert segmentations
2019 - TUHH Open Research
Fully automated longitudinal segmentation of new or enlarging multiple sclerosis (MS) lesions using 3D convolutional neural networks
2019 - TUHH Open Research