Connectomics in NeuroImaging [[electronic resource] ] : 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 |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (X, 139 p. 53 illus., 51 illus. in color.) |
Disciplina | 612.82 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
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 |
ISBN | 3-030-32391-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
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. |
Record Nr. | UNISA-996466447803316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
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 |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (X, 139 p. 53 illus., 51 illus. in color.) |
Disciplina |
612.82
616.80475 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
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 |
ISBN | 3-030-32391-9 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
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. |
Record Nr. | UNINA-9910349275003321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Connectomics in NeuroImaging [[electronic resource] ] : Second International Workshop, CNI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings / / edited by Guorong Wu, Islem Rekik, Markus D. Schirmer, Ai Wern Chung, Brent Munsell |
Edizione | [1st ed. 2018.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
Descrizione fisica | 1 online resource (X, 147 p. 56 illus.) |
Disciplina | 612.82 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Artificial intelligence
Optical data processing Arithmetic and logic units, Computer Mathematical statistics Artificial Intelligence Image Processing and Computer Vision Arithmetic and Logic Structures Probability and Statistics in Computer Science |
ISBN | 3-030-00755-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | 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. |
Record Nr. | UNISA-996466205503316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Connectomics in NeuroImaging : Second International Workshop, CNI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings / / edited by Guorong Wu, Islem Rekik, Markus D. Schirmer, Ai Wern Chung, Brent Munsell |
Edizione | [1st ed. 2018.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
Descrizione fisica | 1 online resource (X, 147 p. 56 illus.) |
Disciplina |
612.82
616.80475 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Artificial intelligence
Optical data processing Arithmetic and logic units, Computer Mathematical statistics Artificial Intelligence Image Processing and Computer Vision Arithmetic and Logic Structures Probability and Statistics in Computer Science |
ISBN | 3-030-00755-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | 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. |
Record Nr. | UNINA-9910349404903321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|