David K. B. Li

According to our database1, David K. B. Li authored at least 16 papers between 2006 and 2020.

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

Timeline

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PhD thesis 
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Links

On csauthors.net:

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

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

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

2011
Myelin water and T<sub>2</sub> relaxation measurements in the healthy cervical spinal cord at 3.0T: Repeatability and changes with age.
NeuroImage, 2011

2010
Optimizing the Use of Radiologist Seed Points for Improved Multiple Sclerosis Lesion Segmentation.
IEEE Trans. Biomed. Eng., 2010

2009
Detection and measurement of coverage loss in interleaved multi-acquisition brain MRIs due to motion-induced inter-slice misalignment.
Medical Image Anal., 2009

2008
Myelin water imaging of multiple sclerosis at 7 T: Correlations with histopathology.
NeuroImage, 2008

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

2006
Reproducibility and reliability of MR measurements in white matter: Clinical implications.
NeuroImage, 2006


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