Titlebook: Connectomics in NeuroImaging; First International Guorong Wu,Paul Laurienti,Brent C. Munsell Conference proceedings 2017 Springer Internat

PAC

A Simple and Efficient Cylinder Imposter Approach to Visualize DTI Fiber Tracts,ased parallel processing systems. Using 10,000 fiber tracts derived from a real DTI scan, we show the rendering speed of our imposter approach is 50% times faster, and requires 900% less memory, when compared visualization approach that uses 3D cylinders.

神化怪物

Revisiting Abnormalities in Brain Network Architecture Underlying Autism Using Topology-Inspired Stining topological data analysis with statistical inference, our results provide evidence of statistically significant network-specific structural abnormalities in autism, from SCNs derived from SN and ECN. These differences in brain architecture are consistent with direct structural analysis using s

interior

個(gè)阿姨勾引你

Early Brain Functional Segregation and Integration Predict Later Cognitive Performance, the triple networks harbor at the medial prefrontal cortex, an ideal brain region for unveiling early development of the high-level functions. Further parcellation of this area indicates consistent subdivisions from 0 to 2 years old, indicating largely predefined functional segregation in this high

Incorporate

dapper

A Whole-Brain Reconstruction Approach for FOD Modeling from Multi-Shell Diffusion MRI,arizations and show that anisotropic regularization produces more robust results across various fiber configurations. We also apply our method to . data from 80 HCP subjects and evaluate the impact of FOD modeling methods on the reconstruction of the challenging fiber bundles from the locus coeruleu

OGLE

The uniform output regulation problem,ific HONs (.-. HONs), . a series of cross-frequency interaction-based HONs (.-. HONs) based on the low-order FC sub-networks constructed at different frequency bands. Both types of these HONs, together with the frequency-specific LONs, are used for the complex network analysis-based feature extracti

GNAW

The uniform output regulation problem,fication method against supervised and unsupervised state-of-the-art methods, while depicting the most discriminative high- and low-order relationships between morphological regions in the left and right hemispheres.

自愛

https://doi.org/10.1007/0-8176-4465-2me-series signals. The FCNet consists of a convolutional neural network that extracts features from time-series signals and a fully connected network that computes the similarity between the extracted features in a Siamese architecture. The functional connectivity computed using FCNet is combined wi

小官

Alexey Pavlov,Nathan Wouw,Henk Nijmeijerecognize the identity of 20 different subjects. The results show person identification models trained with our feature are approximately 30% and 50% more accurate than models trained only using hub-based features and region-to-region features, respectively. Lastly, a . is identified using a neural n