1.

Record Nr.

UNINA9910349275003321

Titolo

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

Pubbl/distr/stampa

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

ISBN

3-030-32391-9

Edizione

[1st ed. 2019.]

Descrizione fisica

1 online resource (X, 139 p. 53 illus., 51 illus. in color.)

Collana

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

Disciplina

612.82

616.80475

Soggetti

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

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Includes index.

Nota di contenuto

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.

Sommario/riassunto

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.