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Christian Wachinger
Christian Wachinger
MIT, Harvard medical school
Verified email at csail.mit.edu - Homepage
Title
Cited by
Cited by
Year
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
9702023
Concurrent spatial and channel ‘squeeze & excitation’in fully convolutional networks
AG Roy, N Navab, C Wachinger
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
9612018
The medical segmentation decathlon
M Antonelli, A Reinke, S Bakas, K Farahani, A Kopp-Schneider, ...
Nature communications 13 (1), 4128, 2022
6902022
ReLayNet: retinal layer and fluid segmentation of macular optical coherence tomography using fully convolutional networks
AG Roy, S Conjeti, SPK Karri, D Sheet, A Katouzian, C Wachinger, ...
Biomedical optics express 8 (8), 3627-3642, 2017
5772017
Recalibrating Fully Convolutional Networks With Spatial and Channel “Squeeze and Excitation” Blocks
AG Roy, N Navab, C Wachinger
IEEE transactions on medical imaging 38 (2), 540-549, 2018
4112018
DeepNAT: Deep convolutional neural network for segmenting neuroanatomy
C Wachinger, M Reuter, T Klein
NeuroImage 170, 434-445, 2018
3842018
Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge
EE Bron, M Smits, WM van der Flier, H Vrenken, F Barkhof, P Scheltens, ...
NeuroImage 111, 562-579, 2015
3602015
BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning
AG Roy, S Siddiqui, S Pölsterl, N Navab, C Wachinger
arXiv preprint arXiv:1905.06731, 2019
3192019
QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy
AG Roy, S Conjeti, N Navab, C Wachinger, ...
NeuroImage 186, 713-727, 2019
2412019
QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy
AG Roy, S Conjeti, N Navab, C Wachinger, ...
NeuroImage 186, 713-727, 2019
2412019
QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy
AG Roy, S Conjeti, N Navab, C Wachinger, ...
NeuroImage 186, 713-727, 2019
2412019
Entropy and Laplacian images: Structural representations for multi-modal registration
C Wachinger, N Navab
Medical Image Analysis 16 (1), 1-17, 2012
1902012
BrainPrint: A discriminative characterization of brain morphology
C Wachinger, P Golland, W Kremen, B Fischl, M Reuter
NeuroImage 109, 232-248, 2015
1702015
‘Squeeze & excite’guided few-shot segmentation of volumetric images
AG Roy, S Siddiqui, S Pölsterl, N Navab, C Wachinger
Medical image analysis 59, 101587, 2020
1562020
‘Squeeze & excite’guided few-shot segmentation of volumetric images
AG Roy, S Siddiqui, S Pölsterl, N Navab, C Wachinger
Medical image analysis 59, 101587, 2020
1562020
Whole-brain analysis reveals increased neuroanatomical asymmetries in dementia for hippocampus and amygdala
C Wachinger, DH Salat, M Weiner, M Reuter
Brain 139 (12), 3253-3266, 2016
1452016
Bayesian QuickNAT: Model uncertainty in deep whole-brain segmentation for structure-wise quality control
AG Roy, S Conjeti, N Navab, C Wachinger, ...
NeuroImage 195, 11-22, 2019
1292019
Domain adaptation for Alzheimer's disease diagnostics
C Wachinger, M Reuter, Alzheimer's Disease Neuroimaging Initiative
Neuroimage 139, 470-479, 2016
1182016
Blockface histology with optical coherence tomography: A comparison with Nissl staining
C Magnain, JC Augustinack, M Reuter, C Wachinger, MP Frosch, ...
NeuroImage 84, 524-533, 2014
1072014
Manifold learning for image-based breathing gating in ultrasound and MRI
C Wachinger, M Yigitsoy, EJ Rijkhorst, N Navab
Medical Image Analysis 16 (4), 806-818, 2012
1022012
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Articles 1–20