Connectomics in NeuroImaging : Third International Workshop, CNI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / edited by Markus D. Schirmer, Archana Venkataraman, Islem Rekik, Minjeong Kim, Ai Wern Chung.

Format:

Book

Contributor:

Schirmer, Markus D., editor.

Venkataraman, Archana, editor.

Rekik, Islem, editor.

Kim, Minjeong, editor.

Chung, Ai Wern, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 11848.

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11848

Language:

English

Subjects (All):

Artificial intelligence.

Data mining.

Computers.

Optical data processing.

Artificial Intelligence.

Data Mining and Knowledge Discovery.

Models and Principles.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Local Subjects:

Artificial Intelligence.

Data Mining and Knowledge Discovery.

Models and Principles.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Physical Description:

1 online resource (X, 139 pages) : 53 illustrations, 51 illustrations in color.

Edition:

First edition 2019.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2019.

System Details:

text file PDF

Summary:

This book constitutes the refereed proceedings of the Third International Workshop on Connectomics in NeuroImaging, CNI 2019, held in conjunction with MICCAI 2019 in Shenzhen, China, in October 2019. The 13 full papers presented were carefully reviewed and selected from 14 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.

Contents:

Unsupervised Feature Selection via Adaptive Embedding and Sparse Learning for Parkinson's Disease Diagnosis

A Novel Graph Neural Network to Localize Eloquent Cortex in Brain Tumor Patients from Resting-State fMRI Connectivity

Graph Morphology-Based Genetic Algorithm for Classifying Late Dementia States

Covariance Shrinkage for Dynamic Functional Connectivity

Rapid Acceleration of the Permutation Test via Transpositions

Heat kernels with functional connectomes reveal atypical energy transport in peripheral subnetworks in autism

A Mass Multivariate Edge-wise Approach for Combining Multiple Connectomes to Improve the Detection of Group Differences

Adversarial Connectome Embedding for Mild Cognitive Impairment Identification using Cortical Morphological Networks

A Machine Learning Framework for Accurate Functional Connectome Fingerprinting and an Application of a Siamese Network

Test-Retest Reliability of Functional Networks for Evaluation of Data-Driven Parcellation

Constraining Disease Progression Models Using Subject Specific Connectivity Priors

Hemodynamic Matrix Factorization for Functional Magnetic Resonance Imaging

Network Dependency Index Stratified Subnetwork Analysis of Functional Connectomes: An application to autism.

Other Format:

Printed edition:

ISBN:

978-3-030-32391-2

9783030323912

Access Restriction:

Restricted for use by site license.