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Hierarchical multi-atlas label fusion with multi-scale feature representation and label-specific patch partition
Authors:G Wu, M Kim, G Sanroma, Q Wang, BC Munsell, D Shen NeuroImage 106, 34-46, 2015
Multi-atlas patch-based label fusion methods have been successfully used to improve segmentation accuracy in many important medical image analysis applications.
Evaluation of machine learning algorithms for treatment outcome prediction in patients with epilepsy based on structural connectome data.
Authors:Brent C. Munsell, Chong-Yaw Wee, Simon S. Keller, Bernd Weber, Christian Elger, Laura Angelica Tomaz da Silva, Travis Nesland, Martin Styner, Dinggang Shen, Leonardo Bonilha
The objective of this study is to evaluate machine learning algorithms aimed at predicting surgical treatment outcomes in groups of patients with temporal lobe epilepsy (TLE) using only the structural brain connectome.
Identifying Abnormal Network Alterations Common to Traumatic Brain Injury and Alzheimer’s Disease Patients Using Functional Connectome Data
Authors:Davy Vanderweyen, Brent C. Munsell , Jacobo E. Mintzer, Olga Mintzer, Andy Gajadhar, Xun Zhu, Guorong Wu, Jane Joseph, Alzheimers Disease Neuroimaging Initiative
The objective of this study is to determine if patients with traumatic brain injury (TBI) have similar pathological changes in brain network organization as patients with Alzheimer’s disease (AD) using functional connectome data