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. | UNINA-9910349404903321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
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 | ||
|
Patch-Based Techniques in Medical Imaging [[electronic resource] ] : First International Workshop, Patch-MI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 9, 2015, Revised Selected Papers / / edited by Guorong Wu, Pierrick Coupé, Yiqiang Zhan, Brent Munsell, Daniel Rueckert |
Edizione | [1st ed. 2015.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
Descrizione fisica | 1 online resource (IX, 216 p. 81 illus. in color.) |
Disciplina | 616.07540285 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Pattern recognition Computer graphics Artificial intelligence Computer simulation Algorithms Image Processing and Computer Vision Pattern Recognition Computer Graphics Artificial Intelligence Simulation and Modeling Algorithm Analysis and Problem Complexity |
ISBN | 3-319-28194-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | A Multi-level Canonical Correlation Analysis Scheme for Standard-dose PET Image Estimation -- Image Super-Resolution by Supervised Adaption of Patchwise Self-Similarity from High-Resolution Image -- Automatic Hippocampus Labeling Using the Hierarchy of Sub-Region Random Forests -- Isointense Infant Brain Segmentation by Stacked Kernel Canonical Correlation Analysis -- Improving Accuracy of Automatic Hippocampus Segmentation in Routine MRI by Features Learned from Ultra-high Field MRI -- Dual-Layer l1-Graph Embedding for Semi-Supervised Image Labeling -- Automatic Liver Tumor Segmentation in Follow-up CT Studies Using Convolutional Neural Network -- Block-based Statistics for Robust Non-Parametric Morphometry -- Automatic Collimation Detection in Digital Radiographs with the Directed Hough Transform and Learning-based Edge Detection -- Efficient Lung Cancer Cell Detection with Deep Convolutional Neural Network -- An Effective Approach for Robust Lung Cancer Cell Detection -- Laplacian Shape Editing with Local Patch Based Force Field for Interactive Segmentation -- Hippocampus Segmentation through Distance Field Fusion -- Learning a Spatiotemporal Dictionary for Magnetic Resonance Fingerprinting with Compress Sensing -- Fast Regions-of-Interest Detection in Whole Slide Histopathology Images -- Reliability Guided Forward and Backward Patch-based Method for Multi-atlas Segmentation -- Correlating Tumour Histology and ex vivo MRI Using Dense Modality-Independent Patch-Based Descriptor -- Multi-Atlas Segmentation using Patch-Based Joint Label Fusion with Non-Negative Least Squares Regression -- A Spatially Constrained Deep Learning Framework for Detection of Epithelial Tumor Nuclei in Cancer Histology Images -- 3D MRI Denoising using Rough Set Theory and Kernel Embedding Method -- A Novel Cell Orientation Congruence Descriptor for Superpixel based Epithelium Segmentation in Endometrial Histology Images -- Patch-based Segmentation from MP2RAGE Images: Comparison to Conventional Techniques -- Multi-Atlas and Multi-Modal Hippocampus Segmentation for Infant MR Brain Images by Propagating Anatomical Labels on Hypergraph -- Prediction of Infant MRI Appearance and Anatomical Structure Evolution using Sparse Patch-based Metamorphosis Learning Framework -- Efficient Multi-Scale Patch-based Segmentation. |
Record Nr. | UNINA-9910483732403321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Patch-Based Techniques in Medical Imaging [[electronic resource] ] : First International Workshop, Patch-MI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 9, 2015, Revised Selected Papers / / edited by Guorong Wu, Pierrick Coupé, Yiqiang Zhan, Brent Munsell, Daniel Rueckert |
Edizione | [1st ed. 2015.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
Descrizione fisica | 1 online resource (IX, 216 p. 81 illus. in color.) |
Disciplina | 616.07540285 |
Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
Soggetto topico |
Optical data processing
Pattern recognition Computer graphics Artificial intelligence Computer simulation Algorithms Image Processing and Computer Vision Pattern Recognition Computer Graphics Artificial Intelligence Simulation and Modeling Algorithm Analysis and Problem Complexity |
ISBN | 3-319-28194-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | A Multi-level Canonical Correlation Analysis Scheme for Standard-dose PET Image Estimation -- Image Super-Resolution by Supervised Adaption of Patchwise Self-Similarity from High-Resolution Image -- Automatic Hippocampus Labeling Using the Hierarchy of Sub-Region Random Forests -- Isointense Infant Brain Segmentation by Stacked Kernel Canonical Correlation Analysis -- Improving Accuracy of Automatic Hippocampus Segmentation in Routine MRI by Features Learned from Ultra-high Field MRI -- Dual-Layer l1-Graph Embedding for Semi-Supervised Image Labeling -- Automatic Liver Tumor Segmentation in Follow-up CT Studies Using Convolutional Neural Network -- Block-based Statistics for Robust Non-Parametric Morphometry -- Automatic Collimation Detection in Digital Radiographs with the Directed Hough Transform and Learning-based Edge Detection -- Efficient Lung Cancer Cell Detection with Deep Convolutional Neural Network -- An Effective Approach for Robust Lung Cancer Cell Detection -- Laplacian Shape Editing with Local Patch Based Force Field for Interactive Segmentation -- Hippocampus Segmentation through Distance Field Fusion -- Learning a Spatiotemporal Dictionary for Magnetic Resonance Fingerprinting with Compress Sensing -- Fast Regions-of-Interest Detection in Whole Slide Histopathology Images -- Reliability Guided Forward and Backward Patch-based Method for Multi-atlas Segmentation -- Correlating Tumour Histology and ex vivo MRI Using Dense Modality-Independent Patch-Based Descriptor -- Multi-Atlas Segmentation using Patch-Based Joint Label Fusion with Non-Negative Least Squares Regression -- A Spatially Constrained Deep Learning Framework for Detection of Epithelial Tumor Nuclei in Cancer Histology Images -- 3D MRI Denoising using Rough Set Theory and Kernel Embedding Method -- A Novel Cell Orientation Congruence Descriptor for Superpixel based Epithelium Segmentation in Endometrial Histology Images -- Patch-based Segmentation from MP2RAGE Images: Comparison to Conventional Techniques -- Multi-Atlas and Multi-Modal Hippocampus Segmentation for Infant MR Brain Images by Propagating Anatomical Labels on Hypergraph -- Prediction of Infant MRI Appearance and Anatomical Structure Evolution using Sparse Patch-based Metamorphosis Learning Framework -- Efficient Multi-Scale Patch-based Segmentation. |
Record Nr. | UNISA-996466368903316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|