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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
Concurrent spatial and channel ‘squeeze & excitation’in fully convolutional networks
AG Roy, N Navab, C Wachinger
International Conference on Medical Image Computing and Computer-Assisted …, 2018
5222018
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
4032017
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy
C Wachinger, M Reuter, T Klein
NeuroImage, 2017
3122017
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
2922015
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
2302018
Entropy and Laplacian images: Structural representations for multi-modal registration
C Wachinger, N Navab
Medical Image Analysis 16 (1), 1-17, 2012
1712012
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
1622019
QuickNAT: A Fully Convolutional Network for Quick and Accurate Segmentation of Neuroanatomy
A Guha Roy, S Conjeti, N Navab, C Wachinger
arXiv preprint arXiv:1801.04161, 2018
162*2018
QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy
A Guha Roy, S Conjeti, N Navab, C Wachinger
arXiv preprint arXiv:1801.04161, 2018
162*2018
BrainPrint: A discriminative characterization of brain morphology
C Wachinger, P Golland, W Kremen, B Fischl, M Reuter
NeuroImage 109, 232-248, 2015
1382015
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
1332019
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
1142016
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
992012
The Medical Segmentation Decathlon
M Antonelli, A Reinke, S Bakas, K Farahani, BA Landman, G Litjens, ...
arXiv preprint arXiv:2106.05735, 2021
982021
Domain adaptation for Alzheimer's disease diagnostics
C Wachinger, M Reuter, Alzheimer's Disease Neuroimaging Initiative
Neuroimage 139, 470-479, 2016
952016
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
932014
‘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
852020
'Squeeze & Excite'Guided Few-Shot Segmentation of Volumetric Images
A Guha Roy, S Siddiqui, S Pölsterl, N Navab, C Wachinger
arXiv preprint arXiv:1902.01314, 2019
85*2019
Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data
AG Roy, S Conjeti, D Sheet, A Katouzian, N Navab, C Wachinger
International Conference on Medical Image Computing and Computer-Assisted …, 2017
832017
Three-dimensional ultrasound mosaicing
C Wachinger, W Wein, N Navab
International Conference on Medical Image Computing and Computer-Assisted …, 2007
802007
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Articles 1–20