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Connectomics in NeuroImaging: Second International Workshop, CNI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings de Guorong Wu

Connectomics in NeuroImaging: Second International Workshop, CNI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings: Lecture Notes in Computer Science, cartea 11083

Editat de Guorong Wu, Islem Rekik, Markus D. Schirmer, Ai Wern Chung, Brent Munsell
en Limba Engleză Paperback – 15 sep 2018
This book constitutes the refereed proceedings of the Second International Workshop on Connectomics in NeuroImaging, CNI 2018, held in conjunction with MICCAI 2018 in Granada, Spain, in September 2018.
The 15 full papers presented were carefully reviewed and selected from 20 submissions. The papers deal with new advancements in network construction, analysis, and visualization techniques in connectomics and their use in clinical diagnosis and group comparison studies as well as in various neuroimaging applications.
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Specificații

ISBN-13: 9783030007546
ISBN-10: 3030007545
Pagini: 144
Ilustrații: X, 147 p. 63 illus., 51 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.23 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Image Processing, Computer Vision, Pattern Recognition, and Graphics

Locul publicării:Cham, Switzerland

Cuprins

Towards Ultra-high Resolution 3D Reconstruction of a Whole Rat Brain from 3D-PLI Data.- FOD-based Registration for Susceptibility Distortion Correction in Connectome Imaging.- GIFE: Efficient and Robust Group-wise Isometric Fiber Embedding.- Multi-Modal Brain Tensor Factorization: Preliminary Results with AD Patients.- Intact Connectional Morphometricity Learning Using Multi-View Morphological Brain Networks with Application to Autism Spectrum Disorder.- Neonatal Morphometric Similarity Networks Predict Atypical Brain Development Associated with Preterm Birth.- Heritability Estimation of Reliable Connectomic Features.- Topological Data Analysis of Functional MRI Connectivity in Time and Space Domains.- Riemannian Regression and Classification Models of Brain Networks Applied to Autism.- Defining Patient Specific Functional Parcellations in Lesional Cohorts via Markov Random Fields.- Data-Specific Feature Selection Method Identification for Most Reproducible Connectomic Feature Discovery Fingerprinting Brain States.- Towards Effective Functional Connectome Fingerprinting.- Connectivity-Driven Brain Parcellation via Consensus Clustering.- GRAND: Unbiased Connectome Atlas of Brain Network by Groupwise Graph Shrinkage and Network Diffusion.- Structural Subnetwork Evolution Across the Lifespan: Rich-club, Feeder, Seeder.