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Roland Opfer
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2020 – today
- 2024
- [c12]Jan Ehrhardt, Hristina Uzunova, Paul Kaftan, Julia Krüger, Roland Opfer, Heinz Handels:
Abstract: Focused Unsupervised Image Registration for Structure-specific Population Analysis. Bildverarbeitung für die Medizin 2024: 52 - [i10]Finn Behrendt, Debayan Bhattacharya, Lennart Maack, Julia Krüger, Roland Opfer, Robin Mieling, Alexander Schlaefer:
Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly Detection. CoRR abs/2403.14262 (2024) - [i9]Finn Behrendt, Debayan Bhattacharya, Robin Mieling, Lennart Maack, Julia Krüger, Roland Opfer, Alexander Schlaefer:
Leveraging the Mahalanobis Distance to enhance Unsupervised Brain MRI Anomaly Detection. CoRR abs/2407.12474 (2024) - 2023
- [c11]Finn Behrendt, Debayan Bhattacharya, Julia Krüger, Roland Opfer, Alexander Schlaefer:
Nodule Detection in Chest Radiographs with Unsupervised Pre-Trained Detection Transformers. ISBI 2023: 1-4 - [c10]Finn Behrendt, Debayan Bhattacharya, Julia Krüger, Roland Opfer, Alexander Schlaefer:
Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI. MIDL 2023: 1019-1032 - [i8]Finn Behrendt, Debayan Bhattacharya, Julia Krüger, Roland Opfer, Alexander Schlaefer
:
Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI. CoRR abs/2303.03758 (2023) - [i7]Finn Behrendt, Debayan Bhattacharya, Robin Mieling, Lennart Maack, Julia Krüger, Roland Opfer, Alexander Schlaefer:
Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs. CoRR abs/2312.04215 (2023) - 2022
- [c9]Finn Behrendt, Marcel Bengs, Frederik Rogge, Julia Krüger, Roland Opfer, Alexander Schlaefer
:
Unsupervised Anomaly Detection in 3D Brain MRI Using Deep Learning with Impured Training Data. ISBI 2022: 1-4 - [c8]Marcel Bengs, Finn Behrendt, Max-Heinrich Laves, Julia Krüger, Roland Opfer, Alexander Schlaefer
:
Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age prediction. Medical Imaging: Computer-Aided Diagnosis 2022 - [i6]Marcel Bengs, Finn Behrendt, Max-Heinrich Laves, Julia Krüger, Roland Opfer, Alexander Schlaefer:
Unsupervised Anomaly Detection in 3D Brain MRI using Deep Learning with Multi-Task Brain Age Prediction. CoRR abs/2201.13081 (2022) - [i5]Finn Behrendt, Marcel Bengs, Frederik Rogge, Julia Krüger, Roland Opfer, Alexander Schlaefer:
Unsupervised Anomaly Detection in 3D Brain MRI using Deep Learning with impured training data. CoRR abs/2204.05778 (2022) - [i4]Finn Behrendt, Debayan Bhattacharya, Julia Krüger, Roland Opfer, Alexander Schlaefer
:
Data-Efficient Vision Transformers for Multi-Label Disease Classification on Chest Radiographs. CoRR abs/2208.08166 (2022) - 2021
- [j3]Marcel Bengs
, Finn Behrendt, Julia Krüger, Roland Opfer, Alexander Schlaefer
:
Three-dimensional deep learning with spatial erasing for unsupervised anomaly segmentation in brain MRI. Int. J. Comput. Assist. Radiol. Surg. 16(9): 1413-1423 (2021) - [i3]Marcel Bengs, Finn Behrendt, Julia Krüger, Roland Opfer, Alexander Schlaefer:
3-Dimensional Deep Learning with Spatial Erasing for Unsupervised Anomaly Segmentation in Brain MRI. CoRR abs/2109.06540 (2021) - 2020
- [j2]Nils Gessert, Julia Krüger, Roland Opfer, Ann-Christin Ostwaldt
, Praveena Manogaran
, Hagen H. Kitzler, Sven Schippling, Alexander Schlaefer
:
Multiple sclerosis lesion activity segmentation with attention-guided two-path CNNs. Comput. Medical Imaging Graph. 84: 101772 (2020) - [i2]Nils Gessert, Marcel Bengs, Julia Krüger, Roland Opfer, Ann-Christin Ostwaldt, Praveena Manogaran, Sven Schippling, Alexander Schlaefer:
4D Deep Learning for Multiple Sclerosis Lesion Activity Segmentation. CoRR abs/2004.09216 (2020) - [i1]Nils Gessert, Julia Krüger, Roland Opfer, Ann-Christin Ostwaldt, Praveena Manogaran, Hagen H. Kitzler, Sven Schippling, Alexander Schlaefer:
Multiple Sclerosis Lesion Activity Segmentation with Attention-Guided Two-Path CNNs. CoRR abs/2008.02001 (2020)
2010 – 2019
- 2010
- [c7]Steffen Renisch, Roland Opfer, Rafael Wiemker:
Towards automatic determination of total tumor burden from PET images. Medical Imaging: Computer-Aided Diagnosis 2010: 76241T
2000 – 2009
- 2009
- [c6]Roland Opfer, Sven Kabus, Torben Schneider, Ingwer C. Carlsen, Steffen Renisch, Jörg Sabczynski:
Follow-up segmentation of lung tumors in PET and CT data. Medical Imaging: Computer-Aided Diagnosis 2009: 72600X - 2008
- [c5]Luyin Zhao, Michael C. Lee, Lilla Böröczky, Victor Vloemans, Roland Opfer:
Comparison of computer-aided diagnosis performance and radiologist readings on the LIDC pulmonary nodule dataset. Medical Imaging: Computer-Aided Diagnosis 2008: 69151I - [c4]Rafael Wiemker, Roland Opfer, Thomas Bülow, Sven Kabus, Ekta Dharaiya:
Repeatability and noise robustness of spicularity features for computer aided characterization of pulmonary nodules in CT. Medical Imaging: Computer-Aided Diagnosis 2008: 691511 - [c3]Roland Opfer, Winfried Brenner, Ingwer Carlsen, Steffen Renisch, Jörg Sabczynski, Rafael Wiemker:
Automatic lesion tracking for a PET/CT based computer aided cancer therapy monitoring system. Medical Imaging: Computer-Aided Diagnosis 2008: 691513 - 2007
- [c2]Rafael Wiemker, Roland Opfer, Thomas Bülow, Patrik Rogalla, Amnon Steinberg, Ekta Dharaiya, Krishna Subramanyan:
Toward computer-aided emphysema quantification on ultralow-dose CT: reproducibility of ventrodorsal gravity effect measurement and correction. Medical Imaging: Computer-Aided Diagnosis 2007: 65140O - [c1]Roland Opfer, Rafael Wiemker:
A new general tumor segmentation framework based on radial basis function energy minimization with a validation study on LIDC lung nodules. Medical Imaging: Image Processing 2007: 651217 - 2006
- [j1]Roland Opfer:
Multiscale kernels. Adv. Comput. Math. 25(4): 357-380 (2006)
Coauthor Index
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last updated on 2024-08-25 20:08 CEST by the dblp team
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