Human brain image alignment has long been an intriguing research topic. The difficulty lies in the huge inter-individual variation. Also, it is not fully understood how structural similarity across subjects is related to functional ...

Several methods have been proposed recently to learn spatiotemporal models of shape progression from repeated observations of several subjects over time, i.e. a longitudinal data set. These methods summarize the population by a single common ...

One of outstanding issues in brain network analysis is to extract common topological substructure shared by a group of individuals. Recently, methods to detect group-wise modular structure on graph Laplacians have been introduced. From the ...

Longitudinal regression analysis for clinical imaging studies is essential to investigate unknown relationships between subject-wise changes over time and subject-specific characteristics, represented by covariates such as disease severity or a ...

Heat diffusion has been widely used in image processing for surface fairing, mesh regularization and surface data smoothing. We present a new fast and accurate numerical method to solve heat diffusion on curved surfaces. This is achieved by ...

Neuroimaging datasets keep growing in size to address increasingly complex medical questions. However, even the largest datasets today alone are too small for training complex machine learning models. A potential solution is to increase sample ...

Medical image synthesis techniques can circumvent the need for costly clinical scan acquisitions using different modalities such as functional Magnetic Resonance Imaging (MRI). Recently, deep learning frameworks were designed to predict a target ...

We introduce a novel switching Markov model for combined epileptic seizure detection and localization from scalp electroencephalography (EEG). Using a hierarchy of Markov chains to fuse multichannel information, our model detects seizure onset, ...

Focal cortical dysplasia (FCD) is a prevalent surgically-amenable epileptogenic malformation of cortical development. On MRI, FCD typically presents with cortical thickening, hyperintensity, and blurring of the gray-white matter interface. These ...

Human brain networks convey important insights in understanding the mechanism of many mental disorders. However, it is difficult to determine a universal optimal among various tractography methods for general diagnosis tasks. To address this issue,...

Brain imaging studies have set the stage for measuring brain function in psychiatric disorders, such as depression, with the goal of developing effective treatment strategies. However, data arising from such studies are often hampered by noise ...

Clinicians implicitly incorporate the complementarity of multi-modal data for disease diagnosis. Often a varied order of importance for this heterogeneous data is considered for personalized decisions. Current learning-based methods have achieved ...

Human brain image alignment based on cortical folding pattern has long been an intriguing yet challenging research topic. Recently, a new gyral folding pattern, termed gyral hinge, was proposed and characterized by the conjunction of gyri from ...