Three-dimensional deep learning with spatial erasing for unsupervised anomaly segmentation in brain MRI
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
In: International Journal of Computer Assisted Radiology and Surgery 16 (9): 1413-1423 (2021-09)
- Event
-
Veröffentlichung
- (where)
-
Hamburg
- (who)
-
Universitätsbibliothek der Technischen Universität Hamburg-Harburg
- (when)
-
2021
- Creator
- DOI
-
10.15480/882.3761
- URN
-
urn:nbn:de:gbv:830-882.0144391
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
25.03.2025, 1:55 PM CET
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Bengs, Marcel
- Behrendt, Finn
- Krüger, Julia
- Opfer, Roland
- Schlaefer, Alexander
- Universitätsbibliothek der Technischen Universität Hamburg-Harburg
Time of origin
- 2021
Other Objects (12)
Anomaly Detection in Brain MRI: From Supervised to Unsupervised Deep Learning
Unsupervised Learning for Anomaly Detection in Medical Images
Autoencoders for unsupervised anomaly detection in high energy physics
Unsupervised Anomaly Detection and Localization for Visual Quality Inspection
Unsupervised Text Segmentation for Automated Error Reduction
Unsupervised text segmentation using semantic relatedness graphs
Unsupervised temporal anomaly detection : Time series, data stream, and interpretability
Uncertainty-based image segmentation with unsupervised mixture models
Diffusion MRI anomaly detection in glioma patients
Consistency regularization for unsupervised domain adaptation in semantic segmentation
MILP Formulations for Unsupervised and Interactive Image Segmentation and Denoising
MILP formulations for unsupervised and interactive image segmentation and denoising
Anomaly Detection in Brain MRI: From Supervised to Unsupervised Deep Learning
Unsupervised Learning for Anomaly Detection in Medical Images
Autoencoders for unsupervised anomaly detection in high energy physics
Unsupervised Anomaly Detection and Localization for Visual Quality Inspection
Unsupervised Text Segmentation for Automated Error Reduction
Unsupervised text segmentation using semantic relatedness graphs
Unsupervised temporal anomaly detection : Time series, data stream, and interpretability
Uncertainty-based image segmentation with unsupervised mixture models
Diffusion MRI anomaly detection in glioma patients
Consistency regularization for unsupervised domain adaptation in semantic segmentation
MILP Formulations for Unsupervised and Interactive Image Segmentation and Denoising
MILP formulations for unsupervised and interactive image segmentation and denoising
Anomaly Detection in Brain MRI: From Supervised to Unsupervised Deep Learning
Unsupervised Learning for Anomaly Detection in Medical Images
Autoencoders for unsupervised anomaly detection in high energy physics
Unsupervised Anomaly Detection and Localization for Visual Quality Inspection
Unsupervised Text Segmentation for Automated Error Reduction
Unsupervised text segmentation using semantic relatedness graphs
Unsupervised temporal anomaly detection : Time series, data stream, and interpretability
Uncertainty-based image segmentation with unsupervised mixture models
Diffusion MRI anomaly detection in glioma patients
Consistency regularization for unsupervised domain adaptation in semantic segmentation
MILP Formulations for Unsupervised and Interactive Image Segmentation and Denoising