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Chapter and Conference Paper
Longitudinal Parcellation of the Infant Cortex Using Multi-modal Connectome Harmonics
Functional segregation and specialization of cortical regions is central to the significant changes that take place during early brain development. We present an automated scheme that harnesses local and long-...
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Chapter and Conference Paper
Pretraining Improves Deep Learning Based Tissue Microstructure Estimation
Diffusion magnetic resonance imaging (dMRI) is commonly used to noninvasively estimate brain tissue microstructure, which provides important biomarkers for studying the structural changes of the brain. Due to the...
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Chapter and Conference Paper
Two Parallel Stages Deep Learning Network for Anterior Visual Pathway Segmentation
The segmentation of the anterior visual pathway(AVP) from MRI sequences is challenging because of the thin long architecture, structural variations along the path, and poor contrast with adjacent anatomic stru...
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Chapter and Conference Paper
q-Space Learning with Synthesized Training Data
q-Space learning has been developed to improve tissue microstructure estimation on diffusion magnetic resonance imaging (dMRI) scans when only a limited number of diffusion gradients are applied. However, the tra...