Anthony Traboulsee

Orcid: 0000-0002-0351-9639

According to our database1, Anthony Traboulsee authored at least 17 papers between 2006 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2020
Myelin water imaging data analysis in less than one minute.
NeuroImage, 2020

2019
Deep learning of brain lesion patterns and user-defined clinical and MRI features for predicting conversion to multiple sclerosis from clinically isolated syndrome.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2019

2017
Hierarchical Multimodal Fusion of Deep-Learned Lesion and Tissue Integrity Features in Brain MRIs for Distinguishing Neuromyelitis Optica from Multiple Sclerosis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Grey Matter Segmentation in Spinal Cord MRIs via 3D Convolutional Encoder Networks with Shortcut Connections.
Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

2016
Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation.
IEEE Trans. Medical Imaging, 2016

Deep Learning of Brain Lesion Patterns for Predicting Future Disease Activity in Patients with Early Symptoms of Multiple Sclerosis.
Proceedings of the Deep Learning and Data Labeling for Medical Applications, 2016

Corpus Callosum Segmentation in Brain MRIs via Robust Target-Localization and Joint Supervised Feature Extraction and Prediction.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

2015
Corpus Callosum Segmentation in MS Studies Using Normal Atlases and Optimal Hybridization of Extrinsic and Intrinsic Image Cues.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

Deep Convolutional Encoder Networks for Multiple Sclerosis Lesion Segmentation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

A sensitive and efficient method for measuring change in cortical thickness using fuzzy correspondence in Alzheimer's disease.
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

2014
Deep Learning of Image Features from Unlabeled Data for Multiple Sclerosis Lesion Segmentation.
Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014

Modeling the Variability in Brain Morphology and Lesion Distribution in Multiple Sclerosis by Deep Learning.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

2008
Complementary information from multi-exponential T<sub>2</sub> relaxation and diffusion tensor imaging reveals differences between multiple sclerosis lesions.
NeuroImage, 2008

SPHARM-Based Spatial fMRI Characterization With Intersubject Anatomical Variability Reduction.
IEEE J. Sel. Top. Signal Process., 2008

Invariant 3D spharm features for characterizing fMRI activations in ROIs while minimizing effects of intersubject anatomical variability.
Proceedings of the 2008 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008

2006
Brain extraction using geodesic active contours.
Proceedings of the Medical Imaging 2006: Image Processing, 2006

Automatic MRI brain tissue segmentation using a hybrid statistical and geometric model.
Proceedings of the 2006 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2006


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