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Deep learning of joint myelin and T1w MRI features in normal-appearing brain tissue to distinguish between multiple sclerosis patients and healthy controls

NeuroImage clinical, 2018-01, Vol.17, p.169-178

2018

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Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation

IEEE transactions on medical imaging, 2016-05, Vol.35 (5), p.1229-1239

2016

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Autonomic Alterations After Pulmonary Vein Isolation in the CIRCA-DOSE (Cryoballoon vs Irrigated Radiofrequency Catheter Ablation) Study

Journal of the American Heart Association, 2021-03, Vol.10 (5), p.e018610-e018610

2021

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Towards large-scale case-finding: training and validation of residual networks for detection of chronic obstructive pulmonary disease using low-dose CT

The Lancet. Digital health, 2020-05, Vol.2 (5), p.e259-e267

2020

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Predicting Atrial Fibrillation Recurrence After Catheter Ablation: A Comparative Evaluation in the CIRCA-DOSE Trial

Circulation. Arrhythmia and electrophysiology, 2021-12, Vol.14 (12), p.e010443-e010443

2021

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Deep learning of brain lesion patterns and user-defined clinical and MRI features for predicting conversion to multiple sclerosis from clinically isolated syndrome

Computer methods in biomechanics and biomedical engineering., 2019-05, Vol.7 (3), p.250-259

2019

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Examining visible articulatory features in clear and plain speech

Speech communication, 2015-12, Vol.75, p.1-13

2015

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Deep Convolutional Encoder Networks for Multiple Sclerosis Lesion Segmentation

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, p.3-11

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Enhancing accuracy of symmetric random walker image registration via a novel data-consistency measure

2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 2016, p.28-31

2016

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Grey Matter Segmentation in Spinal Cord MRIs via 3D Convolutional Encoder Networks with Shortcut Connections

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, p.330-337

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Predicting Catheter Ablation Outcomes with Pre-ablation Heart Rhythm Data: Less Is More

Machine Learning in Medical Imaging, 2020, Vol.12436, p.563-571

2020

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Random walker image registration with inverse consistency

2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 2015, p.837-840

2015

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Random Walks with Efficient Search and Contextually Adapted Image Similarity for Deformable Registration

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, 2013, Vol.16 (Pt 2), p.43-50

2013

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Hierarchical Multimodal Fusion of Deep-Learned Lesion and Tissue Integrity Features in Brain MRIs for Distinguishing Neuromyelitis Optica from Multiple Sclerosis

Medical Image Computing and Computer Assisted Intervention − MICCAI 2017, p.480-488

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Corpus Callosum Segmentation in MS Studies Using Normal Atlases and Optimal Hybridization of Extrinsic and Intrinsic Image Cues

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, p.123-131

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Corpus Callosum Segmentation in Brain MRIs via Robust Target-Localization and Joint Supervised Feature Extraction and Prediction

Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016, Vol.9901, p.406-414

2016

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Deep learning of joint myelin and T1w MRI features in normal-appearing brain tissue to distinguish between multiple sclerosis patients and healthy controls

Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation

Autonomic Alterations After Pulmonary Vein Isolation in the CIRCA-DOSE (Cryoballoon vs Irrigated Radiofrequency Catheter Ablation) Study

Towards large-scale case-finding: training and validation of residual networks for detection of chronic obstructive pulmonary disease using low-dose CT

Predicting Atrial Fibrillation Recurrence After Catheter Ablation: A Comparative Evaluation in the CIRCA-DOSE Trial

Deep learning of brain lesion patterns and user-defined clinical and MRI features for predicting conversion to multiple sclerosis from clinically isolated syndrome

Examining visible articulatory features in clear and plain speech

Deep Convolutional Encoder Networks for Multiple Sclerosis Lesion Segmentation

Enhancing accuracy of symmetric random walker image registration via a novel data-consistency measure

Grey Matter Segmentation in Spinal Cord MRIs via 3D Convolutional Encoder Networks with Shortcut Connections

Predicting Catheter Ablation Outcomes with Pre-ablation Heart Rhythm Data: Less Is More

Random walker image registration with inverse consistency

Random Walks with Efficient Search and Contextually Adapted Image Similarity for Deformable Registration

Hierarchical Multimodal Fusion of Deep-Learned Lesion and Tissue Integrity Features in Brain MRIs for Distinguishing Neuromyelitis Optica from Multiple Sclerosis

Corpus Callosum Segmentation in MS Studies Using Normal Atlases and Optimal Hybridization of Extrinsic and Intrinsic Image Cues

Corpus Callosum Segmentation in Brain MRIs via Robust Target-Localization and Joint Supervised Feature Extraction and Prediction

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