Aaron Carass
Citado por
Citado por
Longitudinal changes in cortical thickness associated with normal aging
M Thambisetty, J Wan, A Carass, Y An, JL Prince, SM Resnick
NeuroImage 52 (4), 1215-1223, 2010
Retinal layer segmentation of macular OCT images using boundary classification
A Lang, A Carass, M Hauser, ES Sotirchos, PA Calabresi, HS Ying, ...
Biomedical optics express 4 (7), 1133-1152, 2013
Longitudinal multiple sclerosis lesion segmentation: resource & challenge
A Carass, S Roy, A Jog, JL Cuzzocreo, E Magrath, A Gherman, J Button, ...
NeuroImage 148 (C), 77-102, 2017
Why rankings of biomedical image analysis competitions should be interpreted with care
L Maier-Hein, M Eisenmann, A Reinke, S Onogur, M Stankovic, P Scholz, ...
Nature communications 9 (1), 5217, 2018
MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans
AM Mendrik, KL Vincken, HJ Kuijf, M Breeuwer, W Bouvy, J de Bresser, ...
Computational Intelligence and Neuroscience, 2015
Cross-modality image synthesis from unpaired data using cyclegan: Effects of gradient consistency loss and training data size
Y Hiasa, Y Otake, M Takao, T Matsuoka, K Takashima, A Carass, ...
Simulation and Synthesis in Medical Imaging: Third International Workshop …, 2018
DeepHarmony: A deep learning approach to contrast harmonization across scanner changes
BE Dewey, C Zhao, JC Reinhold, A Carass, KC Fitzgerald, ES Sotirchos, ...
Magnetic resonance imaging 64, 160-170, 2019
Random Forest Regression for Magnetic Resonance Image Synthesis
A Jog, A Carass, S Roy, DL Pham, JL Prince
Medical Image Analysis 35, 475-488, 2017
Unpaired brain MR-to-CT synthesis using a structure-constrained CycleGAN
H Yang, J Sun, A Carass, C Zhao, J Lee, Z Xu, J Prince
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2018
Evaluating the impact of intensity normalization on MR image synthesis
JC Reinhold, BE Dewey, A Carass, JL Prince
Medical Imaging 2019: Image Processing 10949, 890-898, 2019
Magnetic Resonance Image Example Based Contrast Synthesis
S Roy, A Carass, J Prince
IEEE Transactions on Medical Imaging 32 (12), 2348-2363, 2013
Evaluating white matter lesion segmentations with refined Sørensen-Dice analysis
A Carass, S Roy, A Gherman, JC Reinhold, A Jesson, T Arbel, O Maier, ...
Scientific reports 10 (1), 8242, 2020
The Java Image Science Toolkit (JIST) for rapid prototyping and publishing of neuroimaging software
BC Lucas, JA Bogovic, A Carass, PL Bazin, JL Prince, DL Pham, ...
Neuroinformatics 8, 5-17, 2010
Simple paradigm for extra-cerebral tissue removal: Algorithm and analysis
A Carass, J Cuzzocreo, MB Wheeler, PL Bazin, SM Resnick, JL Prince
NeuroImage 56 (4), 1982-1992, 2011
Consistent cortical reconstruction and multi-atlas brain segmentation
Y Huo, AJ Plassard, A Carass, SM Resnick, DL Pham, JL Prince, ...
NeuroImage 138, 197-210, 2016
Unsupervised MR-to-CT synthesis using structure-constrained CycleGAN
H Yang, J Sun, A Carass, C Zhao, J Lee, JL Prince, Z Xu
IEEE transactions on medical imaging 39 (12), 4249-4261, 2020
Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images
A Carass, JL Cuzzocreo, S Han, CR Hernandez-Castillo, PE Rasser, ...
NeuroImage 183, 150-172, 2018
PET attenuation correction using synthetic CT from ultrashort echo-time MR imaging
S Roy, WT Wang, A Carass, JL Prince, JA Butman, DL Pham
Journal of Nuclear Medicine 55 (12), 2071-2077, 2014
A compressed sensing approach for MR tissue contrast synthesis
S Roy, A Carass, J Prince
Information Processing in Medical Imaging: 22nd International Conference …, 2011
Applications of a deep learning method for anti-aliasing and super-resolution in MRI
C Zhao, M Shao, A Carass, H Li, BE Dewey, LM Ellingsen, J Woo, ...
Magnetic resonance imaging 64, 132-141, 2019
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Artículos 1–20