Volgen
Fernando Navarro
Titel
Geciteerd door
Geciteerd door
Jaar
The liver tumor segmentation benchmark (lits)
P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ...
Medical Image Analysis 84, 102680, 2023
9112023
Generalizability vs. Robustness: Investigating Medical Imaging Networks Using Adversarial Examples
M Paschali, S Conjeti, F Navarro, N Navab
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
174*2018
qPSMA: semiautomatic software for whole-body tumor burden assessment in prostate cancer using 68Ga-PSMA11 PET/CT
A Gafita, M Bieth, M Krönke, G Tetteh, F Navarro, H Wang, E Günther, ...
Journal of Nuclear Medicine 60 (9), 1277-1283, 2019
932019
Deep learning-enabled multi-organ segmentation in whole-body mouse scans
O Schoppe, C Pan, J Coronel, H Mai, Z Rong, MI Todorov, A Müskes, ...
Nature communications 11 (1), 5626, 2020
692020
Shape-aware complementary-task learning for multi-organ segmentation
F Navarro, S Shit, I Ezhov, J Paetzold, A Gafita, JC Peeken, SE Combs, ...
Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019 …, 2019
612019
Tumor sink effect in 68Ga-PSMA-11 PET: myth or reality?
A Gafita, H Wang, A Robertson, WR Armstrong, R Zaum, M Weber, ...
Journal of Nuclear Medicine 63 (2), 226-232, 2022
472022
Optical classification of neoplastic colorectal polyps–a computer-assisted approach (the COACH study)
J Renner, H Phlipsen, B Haller, F Navarro-Avila, Y Saint-Hill-Febles, ...
Scandinavian journal of gastroenterology 53 (9), 1100-1106, 2018
422018
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
372020
Development and external validation of deep-learning-based tumor grading models in soft-tissue sarcoma patients using MR imaging
F Navarro, H Dapper, R Asadpour, C Knebel, MB Spraker, V Schwarze, ...
Cancers 13 (12), 2866, 2021
302021
Grading loss: a fracture grade-based metric loss for vertebral fracture detection
M Husseini, A Sekuboyina, M Loeffler, F Navarro, BH Menze, JS Kirschke
Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020
242020
Geometry-aware neural solver for fast Bayesian calibration of brain tumor models
I Ezhov, T Mot, S Shit, J Lipkova, JC Paetzold, F Kofler, C Pellegrini, ...
IEEE Transactions on Medical Imaging 41 (5), 1269-1278, 2021
20*2021
Evaluating the robustness of self-supervised learning in medical imaging
F Navarro, C Watanabe, S Shit, A Sekuboyina, JC Peeken, SE Combs, ...
arXiv preprint arXiv:2105.06986, 2021
202021
Automated detection of the contrast phase in MDCT by an artificial neural network improves the accuracy of opportunistic bone mineral density measurements
S Rühling, F Navarro, A Sekuboyina, M El Husseini, T Baum, B Menze, ...
European Radiology, 1-10, 2022
182022
Webly supervised learning for skin lesion classification
F Navarro, S Conjeti, F Tombari, N Navab
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
182018
Suprosanna Shit, Ivan Ezhov, Johannes Paetzold, Andrei Gafita, Jan C Peeken, Stephanie E Combs, and Bjoern H Menze. Shape-aware complementary-task learning for multi-organ …
F Navarro
Machine Learning in Medical Imaging, 620-627, 2019
112019
Robust, primitive, and unsupervised quality estimation for segmentation ensembles
F Kofler, I Ezhov, L Fidon, CM Pirkl, JC Paetzold, E Burian, S Pati, ...
Frontiers in Neuroscience 15, 752780, 2021
72021
Focused decoding enables 3D anatomical detection by transformers
B Wittmann, F Navarro, S Shit, B Menze
arXiv preprint arXiv:2207.10774, 2022
42022
A Unified 3D Framework for Organs-at-Risk Localization and Segmentation for Radiation Therapy Planning
F Navarro, G Sasahara, S Shit, A Sekuboyina, I Ezhov, JC Peeken, ...
2022 44th Annual International Conference of the IEEE Engineering in …, 2022
42022
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
42020
A deep learning approach to predict collateral flow in stroke patients using radiomic features from perfusion images
G Tetteh, F Navarro, R Meier, J Kaesmacher, JC Paetzold, JS Kirschke, ...
Frontiers in neurology 14, 1039693, 2023
32023
Het systeem kan de bewerking nu niet uitvoeren. Probeer het later opnieuw.
Artikelen 1–20