Connectomics in NeuroImaging

Second International Workshop, CNI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings

AvGuorong Wu,Islem Rekik

Häftad, Engelska, 2018

Del 11083 i serien Lecture Notes in Computer Science

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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.

Produktinformation

Utgivningsdatum:2018-09-15
Mått:155 x 235 x 9 mm
Vikt:254 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:147
Förlag:Springer Nature Switzerland AG
ISBN:9783030007546

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT
Hårdvara inom Data och IT

Innehållsförteckning

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.

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Second International Workshop, CNI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings

AvGuorong Wu,Islem Rekik

Häftad, Engelska, 2018

Del 11083 i serien Lecture Notes in Computer Science

573 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Fler format och utgåvor

Häftad

573 kr

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573 kr

Beskrivning

Produktinformation

Utgivningsdatum:2018-09-15
Mått:155 x 235 x 9 mm
Vikt:254 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:147
Förlag:Springer Nature Switzerland AG
ISBN:9783030007546

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT
Hårdvara inom Data och IT

Innehållsförteckning

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.

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