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Julia Krüger
Julia Krüger
Researcher, jung diagnostics GmbH
Verified email at jung-diagnostics.de
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Year
Multiple sclerosis lesion activity segmentation with attention-guided two-path CNNs
N Gessert, J Krüger, R Opfer, AC Ostwaldt, P Manogaran, HH Kitzler, ...
Computerized Medical Imaging and Graphics 84, 101772, 2020
442020
Fully automated longitudinal segmentation of new or enlarged multiple sclerosis lesions using 3D convolutional neural networks
J Krüger, R Opfer, N Gessert, AC Ostwaldt, P Manogaran, HH Kitzler, ...
NeuroImage: Clinical 28, 102445, 2020
432020
Three-dimensional deep learning with spatial erasing for unsupervised anomaly segmentation in brain MRI
M Bengs, F Behrendt, J Krüger, R Opfer, A Schlaefer
International journal of computer assisted radiology and surgery 16 (9 …, 2021
242021
4D deep learning for multiple sclerosis lesion activity segmentation
N Gessert, M Bengs, J Krüger, R Opfer, AC Ostwaldt, P Manogaran, ...
arXiv preprint arXiv:2004.09216, 2020
172020
Statistical appearance models based on probabilistic correspondences
J Krüger, J Ehrhardt, H Handels
Medical image analysis 37, 146-159, 2017
152017
Simulation of mammographic breast compression in 3D MR images using ICP-based B-spline deformation for multimodality breast cancer diagnosis
J Krüger, J Ehrhardt, A Bischof, H Handels
International journal of computer assisted radiology and surgery 9 (3), 367-377, 2014
142014
Automatic segmentation of the thalamus using a massively trained 3D convolutional neural network: higher sensitivity for the detection of reduced thalamus volume by improved …
R Opfer, J Krüger, L Spies, AC Ostwaldt, HH Kitzler, S Schippling, ...
European Radiology, 1-10, 2022
122022
Breast compression simulation using ICP-based B-spline deformation for correspondence analysis in mammography and MRI datasets
J Krüger, J Ehrhardt, A Bischof, H Handels
Medical Imaging 2013: Image Processing 8669, 86691D, 2013
112013
Registration with probabilistic correspondences—Accurate and robust registration for pathological and inhomogeneous medical data
J Krüger, S Schultz, H Handels, J Ehrhardt
Computer Vision and Image Understanding 190, 102839, 2020
102020
Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age prediction
M Bengs, F Behrendt, MH Laves, J Krüger, R Opfer, A Schlaefer
Medical Imaging 2022: Computer-Aided Diagnosis 12033, 291-295, 2022
82022
Infratentorial lesions in multiple sclerosis patients: intra-and inter-rater variability in comparison to a fully automated segmentation using 3D convolutional neural networks
J Krüger, AC Ostwaldt, L Spies, B Geisler, A Schlaefer, HH Kitzler, ...
European radiology 32 (4), 2798-2809, 2022
82022
Bayesian inference for uncertainty quantification in point-based deformable image registration
S Schultz, J Krüger, H Handels, J Ehrhardt
Medical Imaging 2019: Image Processing 10949, 109491S, 2019
82019
Capturing Inter-Slice Dependencies of 3D Brain MRI-Scans for Unsupervised Anomaly Detection
F Behrendt, M Bengs, D Bhattacharya, J Krüger, R Opfer, A Schlaefer
Medical Imaging with Deep Learning, 2022
62022
Unsupervised Anomaly Detection in 3D Brain MRI using Deep Learning with impured training data
F Behrendt, M Bengs, F Rogge, J Krüger, R Opfer, A Schlaefer
2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 1-4, 2022
62022
Single-subject analysis of regional brain volumetric measures can be strongly influenced by the method for head size adjustment
R Opfer, J Krüger, L Spies, HH Kitzler, S Schippling, R Buchert
Neuroradiology, 1-9, 2022
52022
Fully automated longitudinal segmentation of new or enlarging Multiple Scleroses (MS) lesions using 3D convolution neural networks
J Krüger, R Opfer, N Gessert, A Ostwaldt, C Walker-Egger, P Manogaran, ...
RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden …, 2020
52020
Age-dependent cut-offs for pathological deep gray matter and thalamic volume loss using Jacobian integration
R Opfer, J Krüger, L Spies, M Hamann, CA Wicki, HH Kitzler, C Gocke, ...
NeuroImage: Clinical 28, 102478, 2020
52020
Estimation of corresponding locations in ipsilateral mammograms: a comparison of different methods
M Wilms, J Krüger, M Marx, J Ehrhardt, A Bischof, H Handels
Medical Imaging 2015: Computer-Aided Diagnosis 9414, 94142B, 2015
52015
Statistical shape and appearance models without one-to-one correspondences
J Ehrhardt, J Krüger, H Handels
Medical Imaging 2014: Image Processing 9034, 90340U, 2014
52014
A maximum-a-posteriori framework for statistical appearance models with probabilistic correspondences
J Krüger, J Ehrhardt, H Handels
Bayesian and grAphical Models for Biomedical Imaging, 2015
32015
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