Sarah H. Ying

According to our database1, Sarah H. Ying authored at least 21 papers between 2011 and 2019.

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Bibliography

2019
Automatic quality control using hierarchical shape analysis for cerebellum parcellation.
Proceedings of the Medical Imaging 2019: Image Processing, 2019

Cerebellum parcellation with convolutional neural networks.
Proceedings of the Medical Imaging 2019: Image Processing, 2019

2018
Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images.
NeuroImage, 2018

2017
EEG Classification with a Sequential Decision-Making Method in Motor Imagery BCI.
Int. J. Neural Syst., 2017

2016
Automated cerebellar lobule segmentation with application to cerebellar structural analysis in cerebellar disease.
NeuroImage, 2016

Landmark based shape analysis for cerebellar ataxia classification and cerebellar atrophy pattern visualization.
Proceedings of the Medical Imaging 2016: Image Processing, 2016

Quality assurance using outlier detection on an automatic segmentation method for the cerebellar peduncles.
Proceedings of the Medical Imaging 2016: Image Processing, 2016

A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

2015
Segmentation of the Cerebellar Peduncles Using a Random Forest Classifier and a Multi-object Geometric Deformable Model: Application to Spinocerebellar Ataxia Type 6.
Neuroinformatics, 2015

2014
Deep Learning for Cerebellar Ataxia Classification and Functional Score Regression.
Proceedings of the Machine Learning in Medical Imaging - 5th International Workshop, 2014

Automatic Method for Thalamus Parcellation Using Multi-modal Feature Classification.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

2013
Approaching expert results using a hierarchical cerebellum parcellation protocol for multiple inexpert human raters.
NeuroImage, 2013

Parcellation of the thalamus using diffusion tensor images and a multi-object geometric deformable model.
Proceedings of the Medical Imaging 2013: Image Processing, 2013

Segmentation of the complete superior cerebellar peduncles using a multi-object geometric deformable model.
Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

Thalamic parcellation from multi-modal data using random forest learning.
Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

Automated Segmentation of the Cerebellar Lobules Using Boundary Specific Classification and Evolution.
Proceedings of the Information Processing in Medical Imaging, 2013

2012
A fiber tracking method guided by volumetric tract segmentation.
Proceedings of the 2012 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, 2012

Labeling of the cerebellar peduncles using a supervised Gaussian classifier with volumetric tract segmentation.
Proceedings of the Medical Imaging 2012: Image Processing, 2012

Fully automatic segmentation of the dentate nucleus using diffusion weighted images.
Proceedings of the 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2012

2011
Superficially Located White Matter Structures Commonly Seen in the Human and the Macaque Brain with Diffusion Tensor Imaging.
Brain Connect., 2011

Improved BCI performance with sequential hypothesis testing.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011


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