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Diana Waldmannstetter
Diana Waldmannstetter
PhD Candidate, Technical University of Munich (TUM)
Verified email at tum.de
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Cited by
Year
Brats toolkit: translating brats brain tumor segmentation algorithms into clinical and scientific practice
F Kofler, C Berger, D Waldmannstetter, J Lipkova, I Ezhov, G Tetteh, ...
Frontiers in neuroscience 14, 125, 2020
1032020
The brain tumor sequence registration challenge: establishing correspondence between pre-operative and follow-up MRI scans of diffuse glioma patients
B Baheti, D Waldmannstetter, S Chakrabarty, H Akbari, M Bilello, ...
arXiv preprint arXiv:2112.06979, 2021
502021
Coarse-to-fine adversarial networks and zone-based uncertainty analysis for NK/T-cell lymphoma segmentation in CT/PET images
X Hu, R Guo, J Chen, H Li, D Waldmannstetter, Y Zhao, B Li, K Shi, ...
IEEE journal of biomedical and health informatics 24 (9), 2599-2608, 2020
482020
Deep reinforcement learning for organ localization in CT
F Navarro, A Sekuboyina, D Waldmannstetter, JC Peeken, SE Combs, ...
Medical Imaging with Deep Learning, 544-554, 2020
442020
Learn-Morph-Infer: a new way of solving the inverse problem for brain tumor modeling
I Ezhov, K Scibilia, K Franitza, F Steinbauer, S Shit, L Zimmer, J Lipkova, ...
Medical Image Analysis 83, 102672, 2023
192023
Benchmarking the cow with the topcow challenge: Topology-aware anatomical segmentation of the circle of willis for cta and mra
K Yang, F Musio, Y Ma, N Juchler, JC Paetzold, R Al-Maskari, L Höher, ...
ArXiv, 2023
162023
The brain tumor segmentation (brats) challenge 2023: Local synthesis of healthy brain tissue via inpainting
F Kofler, F Meissen, F Steinbauer, R Graf, E Oswald, E de da Rosa, HB Li, ...
arXiv preprint arXiv:2305.08992, 2023
142023
Deep learning-based parameter mapping for joint relaxation and diffusion tensor MR Fingerprinting
CM Pirk, PA Gómez, I Lipp, G Buonincontri, M Molina-Romero, ...
Medical Imaging with Deep Learning, 638-654, 2020
142020
Learning residual motion correction for fast and robust 3D multiparametric MRI
CM Pirkl, M Cencini, JW Kurzawski, D Waldmannstetter, H Li, ...
Medical Image Analysis 77, 102387, 2022
112022
Deep learning-enabled diffusion tensor MR fingerprinting
CM Pirkl, I Lipp, G Buonincontri, M Molina-Romero, A Sekuboyina, ...
Proc. 27th Annu. Meet (ISMRM), 1102, 2019
92019
Reinforced redetection of landmark in pre-and post-operative brain scan using anatomical guidance for image alignment
D Waldmannstetter, F Navarro, B Wiestler, JS Kirschke, A Sekuboyina, ...
Biomedical Image Registration: 9th International Workshop, WBIR 2020 …, 2020
72020
Spatial-frequency non-local convolutional lstm network for prcc classification
Y Zhao, Y Liu, Y Kan, A Sekuboyina, D Waldmannstetter, H Li, X Hu, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
32019
Toward image-based personalization of glioblastoma therapy: A clinical and biological validation study of a novel, deep learning-driven tumor growth model
MC Metz, I Ezhov, JC Peeken, JA Buchner, J Lipkova, F Kofler, ...
Neuro-Oncology Advances 6 (1), vdad171, 2024
22024
Framing image registration as a landmark detection problem for better representation of clinical relevance
D Waldmannstetter, B Wiestler, J Schwarting, I Ezhov, M Metz, S Bakas, ...
arXiv preprint arXiv:2308.01318, 2023
22023
Towards Image-Based Personalization of Glioblastoma Therapy A Clinical and Biological Validation Study of a Novel, Deep Learning-Driven Tumor Growth Model
MC Metz, I Ezhov, L Zimmer, JC Peeken, JA Buchner, J Lipkova, F Kofler, ...
22023
Quantitative evaluation of the influence of multiple MRI sequences and of pathological tissues on the registration of longitudinal data acquired during brain tumor treatment
L Canalini, J Klein, D Waldmannstetter, F Kofler, S Cerri, A Hering, ...
Frontiers in Neuroimaging 1, 977491, 2022
22022
QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge
HB Li, F Navarro, I Ezhov, A Bayat, D Das, F Kofler, S Shit, ...
arXiv preprint arXiv:2405.18435, 2024
12024
Residual learning for 3D motion corrected quantitative MRI: Robust clinical T1, T2 and proton density mapping
C Pirkl, M Cencini, JW Kurzawski, D Waldmannstetter, H Li, A Sekuboyina, ...
Medical Imaging with Deep Learning, 2021
12021
Primitive Simultaneous Optimization of Similarity Metrics for Image Registration
D Waldmannstetter, B Wiestler, J Schwarting, I Ezhov, M Metz, S Bakas, ...
arXiv preprint arXiv:2304.01601, 2023
2023
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