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Connectomics in NeuroImaging [[electronic resource] ] : First International Workshop, CNI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Proceedings / / edited by Guorong Wu, Paul Laurienti, Leonardo Bonilha, Brent C. Munsell
| Connectomics in NeuroImaging [[electronic resource] ] : First International Workshop, CNI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Proceedings / / edited by Guorong Wu, Paul Laurienti, Leonardo Bonilha, Brent C. Munsell |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (VIII, 171 p. 67 illus.) |
| Disciplina | 612.82 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Computer graphics Pattern recognition Computer organization Computer science—Mathematics Image Processing and Computer Vision Artificial Intelligence Computer Graphics Pattern Recognition Computer Systems Organization and Communication Networks Discrete Mathematics in Computer Science |
| ISBN | 3-319-67159-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Connectome of Autistic Brains, Global Versus Local Characterization -- 1 Introduction -- 1.1 Connectomes and Autism Spectrum Disorder -- 1.2 Global Metrics -- 1.3 Local Connectivity Differences -- 2 Methods -- 3 Data and Experimental Settings -- 3.1 Pre-processing and Connectome Construction -- 3.2 Experimental Settings -- 4 Results and Discussions -- 5 Conclusion -- References -- Constructing Multi-frequency High-Order Functional Connectivity Network for Diagnosis of Mild Cognit ... -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Multi-frequency High-Order FC Networks -- 2.2 Feature Extraction and Classification -- 3 Experiments -- 3.1 Data -- 3.2 Performance Evaluation -- 3.3 Intra-spectrum and Inter-spectrum HONs -- 4 Conclusion -- Acknowledgements -- References -- Consciousness Level and Recovery Outcome Prediction Using High-Order Brain Functional Connectivity N ... -- Abstract -- 1 Introduction -- 2 Materials -- 3 High-Order BFCN Construction -- 4 Experiments -- 5 Conclusion -- Acknowledgements -- References -- Discriminative Log-Euclidean Kernels for Learning on Brain Networks -- 1 Introduction -- 2 Methods and Materials -- 2.1 Subjects -- 2.2 Image Data -- 2.3 Image Processing -- 2.4 Brain Network Construction -- 2.5 Gaussian Process Classification -- 2.6 The Discriminative Log-Euclidean Kernel -- 2.7 Impementation Details -- 2.8 Classification Experiments -- 2.9 Group Difference Experiments -- 3 Results and Discussion -- 4 Conclusions -- References -- Interactive Computation and Visualization of Structural Connectomes in Real-Time -- 1 Introduction -- 2 Methods -- 2.1 Structural Connectivity -- 3 Visualization -- 4 Results -- 5 Discussion -- 6 Conclusion -- References.
Pairing-based Ensemble Classifier Learning using Convolutional Brain Multiplexes and Multi-view Brain Networks for Early Dementia Diagnosis -- 1 Introduction -- 2 Ensemble Classifier Using Paired CCA-Mapped Convolutional Brain Mutliplexes for eMCI/NC Classification -- 3 Results and Discussion -- 4 Conclusion -- References -- High-order Connectomic Manifold Learning for Autistic Brain State Identification -- 1 Introduction -- 2 High-Order Connectomic Manifold Learning for Unsupervised Clustering of Autistic and Healthy Brains -- 3 Results and Discussion -- 4 Conclusion -- References -- A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort -- 1 Introduction -- 2 Generative Model of Abnormal Communities -- 3 Population Study of Autism -- 4 Conclusion -- References -- FCNet: A Convolutional Neural Network for Calculating Functional Connectivity from Functional MRI -- 1 Introduction -- 2 Method -- 2.1 Data and Preprocessing -- 2.2 Functional Connectivity Through FCNet -- 2.3 Feature Selection and Classification -- 3 Experiments and Results -- 4 Conclusion -- References -- Identifying Subnetwork Fingerprints in Structural Connectomes: A Data-Driven Approach -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Participants, MRI Acquisition, and Connectome Reconstruction -- 2.2 Subnetwork Feature -- 2.3 Person Identification Model and Performance Evaluation -- 2.4 Feature Selection and Majority Vote Subnetwork Feature -- 3 Results -- 4 Discussion -- 5 Conclusion -- Acknowledgement -- References -- A Simple and Efficient Cylinder Imposter Approach to Visualize DTI Fiber Tracts -- Abstract -- 1 Introduction -- 2 Proposed Method -- 2.1 Cylinder Imposter -- 2.2 End Imposter -- 3 Experiments -- 4 Limitations -- 5 Conclusion -- 6 Implementation -- References. Revisiting Abnormalities in Brain Network Architecture Underlying Autism Using Topology-Inspired Statistical Inference -- 1 Introduction -- 2 Technical Background -- 2.1 Structural Covariance Network -- 2.2 Graph Filtration -- 2.3 Statistical Inference -- 3 Methods -- 3.1 Data Preprocessing -- 3.2 Structural Covariance Networks and Statistical Inference -- 4 Results -- 5 Conclusion and Discussion -- References -- "Evaluating Acquisition Time of rfMRI in the Human Connectome Project for Early Psychosis. How Much ... -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Participants -- 2.2 Data Acquisition -- 2.3 Data Preprocessing -- 2.4 Statistical Analysis -- 3 Results -- 3.1 Correlation Matrix Reliability -- 3.2 Network Rank Reliability -- 4 Discussion and Conclusion -- Acknowledgments -- References -- Early Brain Functional Segregation and Integration Predict Later Cognitive Performance -- Abstract -- 1 Introduction -- 2 Methods and Results -- 2.1 An Early Developing Triple Network Model -- 2.2 Individual Prediction of Later Cognitive Performance -- 3 Discussion and Conclusions -- 4 Future Works and Clinical Implications -- References -- Measuring Brain Connectivity via Shape Analysis of fMRI Time Courses and Spectra -- 1 Introduction -- 2 FMRI Shape Analysis of Time Courses and Spectra -- 2.1 Elastic Functional Data Analysis of fMRI Signals Using SRVFs -- 2.2 fMRI Alignment and Registration: -- 3 Results -- 3.1 Visualization of Elastic Functional Alignment -- 3.2 Measuring Brain Connectivity After Elastic fMRI Alignment -- 4 Discussion -- References -- Topological Network Analysis of Electroencephalographic Power Maps -- 1 Introduction -- 2 Methods -- 3 Simulations -- 4 Real Data Application -- 5 Discussion -- References -- Region-Wise Stochastic Pattern Modeling for Autism Spectrum Disorder Identification and Temporal Dynamics Analysis. 1 Introduction -- 2 Materials and Image Processing -- 3 ROI-Wise Temporal Dynamics Estimation -- 3.1 ROI-Wise HMMs Modeling -- 3.2 Feature Extraction and Classifier Learning -- 3.3 Measuring Temporal Dynamics -- 4 Experimental Settings and Results -- 4.1 Choosing Optimal Number of States in HMMs -- 4.2 Performance Comparison -- 4.3 Regional Importance and Temporal Dynamics Analysis -- 5 Conclusion -- References -- A Whole-Brain Reconstruction Approach for FOD Modeling from Multi-Shell Diffusion MRI -- 1 Introduction -- 2 Method -- 2.1 Voxel-Wise FOD Modeling from Multi-Shell Imaging -- 2.2 Whole-Brain FOD Modeling with Spatial Regularity -- 2.3 Spatial Regularization via Hyper-spherical Smoothing -- 3 Experiments -- 3.1 Simulation -- 3.2 HCP Data for Locus Coeruleus Bundle Reconstruction -- 4 Discussion and Conclusion -- References -- Topological Distances Between Brain Networks -- 1 Introduction -- 2 Matrix Norms -- 3 Gromov-Hausdorff Distance -- 4 Kolmogorov-Smirnov Distance -- 5 Comparisons -- 6 Application -- 7 Discussion -- References -- Author Index. |
| Record Nr. | UNISA-996466266203316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Connectomics in NeuroImaging : First International Workshop, CNI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Proceedings / / edited by Guorong Wu, Paul Laurienti, Leonardo Bonilha, Brent C. Munsell
| Connectomics in NeuroImaging : First International Workshop, CNI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Proceedings / / edited by Guorong Wu, Paul Laurienti, Leonardo Bonilha, Brent C. Munsell |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (VIII, 171 p. 67 illus.) |
| Disciplina | 612.82 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Computer graphics Pattern recognition Computer organization Computer science—Mathematics Image Processing and Computer Vision Artificial Intelligence Computer Graphics Pattern Recognition Computer Systems Organization and Communication Networks Discrete Mathematics in Computer Science |
| ISBN | 3-319-67159-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Connectome of Autistic Brains, Global Versus Local Characterization -- 1 Introduction -- 1.1 Connectomes and Autism Spectrum Disorder -- 1.2 Global Metrics -- 1.3 Local Connectivity Differences -- 2 Methods -- 3 Data and Experimental Settings -- 3.1 Pre-processing and Connectome Construction -- 3.2 Experimental Settings -- 4 Results and Discussions -- 5 Conclusion -- References -- Constructing Multi-frequency High-Order Functional Connectivity Network for Diagnosis of Mild Cognit ... -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Multi-frequency High-Order FC Networks -- 2.2 Feature Extraction and Classification -- 3 Experiments -- 3.1 Data -- 3.2 Performance Evaluation -- 3.3 Intra-spectrum and Inter-spectrum HONs -- 4 Conclusion -- Acknowledgements -- References -- Consciousness Level and Recovery Outcome Prediction Using High-Order Brain Functional Connectivity N ... -- Abstract -- 1 Introduction -- 2 Materials -- 3 High-Order BFCN Construction -- 4 Experiments -- 5 Conclusion -- Acknowledgements -- References -- Discriminative Log-Euclidean Kernels for Learning on Brain Networks -- 1 Introduction -- 2 Methods and Materials -- 2.1 Subjects -- 2.2 Image Data -- 2.3 Image Processing -- 2.4 Brain Network Construction -- 2.5 Gaussian Process Classification -- 2.6 The Discriminative Log-Euclidean Kernel -- 2.7 Impementation Details -- 2.8 Classification Experiments -- 2.9 Group Difference Experiments -- 3 Results and Discussion -- 4 Conclusions -- References -- Interactive Computation and Visualization of Structural Connectomes in Real-Time -- 1 Introduction -- 2 Methods -- 2.1 Structural Connectivity -- 3 Visualization -- 4 Results -- 5 Discussion -- 6 Conclusion -- References.
Pairing-based Ensemble Classifier Learning using Convolutional Brain Multiplexes and Multi-view Brain Networks for Early Dementia Diagnosis -- 1 Introduction -- 2 Ensemble Classifier Using Paired CCA-Mapped Convolutional Brain Mutliplexes for eMCI/NC Classification -- 3 Results and Discussion -- 4 Conclusion -- References -- High-order Connectomic Manifold Learning for Autistic Brain State Identification -- 1 Introduction -- 2 High-Order Connectomic Manifold Learning for Unsupervised Clustering of Autistic and Healthy Brains -- 3 Results and Discussion -- 4 Conclusion -- References -- A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort -- 1 Introduction -- 2 Generative Model of Abnormal Communities -- 3 Population Study of Autism -- 4 Conclusion -- References -- FCNet: A Convolutional Neural Network for Calculating Functional Connectivity from Functional MRI -- 1 Introduction -- 2 Method -- 2.1 Data and Preprocessing -- 2.2 Functional Connectivity Through FCNet -- 2.3 Feature Selection and Classification -- 3 Experiments and Results -- 4 Conclusion -- References -- Identifying Subnetwork Fingerprints in Structural Connectomes: A Data-Driven Approach -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Participants, MRI Acquisition, and Connectome Reconstruction -- 2.2 Subnetwork Feature -- 2.3 Person Identification Model and Performance Evaluation -- 2.4 Feature Selection and Majority Vote Subnetwork Feature -- 3 Results -- 4 Discussion -- 5 Conclusion -- Acknowledgement -- References -- A Simple and Efficient Cylinder Imposter Approach to Visualize DTI Fiber Tracts -- Abstract -- 1 Introduction -- 2 Proposed Method -- 2.1 Cylinder Imposter -- 2.2 End Imposter -- 3 Experiments -- 4 Limitations -- 5 Conclusion -- 6 Implementation -- References. Revisiting Abnormalities in Brain Network Architecture Underlying Autism Using Topology-Inspired Statistical Inference -- 1 Introduction -- 2 Technical Background -- 2.1 Structural Covariance Network -- 2.2 Graph Filtration -- 2.3 Statistical Inference -- 3 Methods -- 3.1 Data Preprocessing -- 3.2 Structural Covariance Networks and Statistical Inference -- 4 Results -- 5 Conclusion and Discussion -- References -- "Evaluating Acquisition Time of rfMRI in the Human Connectome Project for Early Psychosis. How Much ... -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Participants -- 2.2 Data Acquisition -- 2.3 Data Preprocessing -- 2.4 Statistical Analysis -- 3 Results -- 3.1 Correlation Matrix Reliability -- 3.2 Network Rank Reliability -- 4 Discussion and Conclusion -- Acknowledgments -- References -- Early Brain Functional Segregation and Integration Predict Later Cognitive Performance -- Abstract -- 1 Introduction -- 2 Methods and Results -- 2.1 An Early Developing Triple Network Model -- 2.2 Individual Prediction of Later Cognitive Performance -- 3 Discussion and Conclusions -- 4 Future Works and Clinical Implications -- References -- Measuring Brain Connectivity via Shape Analysis of fMRI Time Courses and Spectra -- 1 Introduction -- 2 FMRI Shape Analysis of Time Courses and Spectra -- 2.1 Elastic Functional Data Analysis of fMRI Signals Using SRVFs -- 2.2 fMRI Alignment and Registration: -- 3 Results -- 3.1 Visualization of Elastic Functional Alignment -- 3.2 Measuring Brain Connectivity After Elastic fMRI Alignment -- 4 Discussion -- References -- Topological Network Analysis of Electroencephalographic Power Maps -- 1 Introduction -- 2 Methods -- 3 Simulations -- 4 Real Data Application -- 5 Discussion -- References -- Region-Wise Stochastic Pattern Modeling for Autism Spectrum Disorder Identification and Temporal Dynamics Analysis. 1 Introduction -- 2 Materials and Image Processing -- 3 ROI-Wise Temporal Dynamics Estimation -- 3.1 ROI-Wise HMMs Modeling -- 3.2 Feature Extraction and Classifier Learning -- 3.3 Measuring Temporal Dynamics -- 4 Experimental Settings and Results -- 4.1 Choosing Optimal Number of States in HMMs -- 4.2 Performance Comparison -- 4.3 Regional Importance and Temporal Dynamics Analysis -- 5 Conclusion -- References -- A Whole-Brain Reconstruction Approach for FOD Modeling from Multi-Shell Diffusion MRI -- 1 Introduction -- 2 Method -- 2.1 Voxel-Wise FOD Modeling from Multi-Shell Imaging -- 2.2 Whole-Brain FOD Modeling with Spatial Regularity -- 2.3 Spatial Regularization via Hyper-spherical Smoothing -- 3 Experiments -- 3.1 Simulation -- 3.2 HCP Data for Locus Coeruleus Bundle Reconstruction -- 4 Discussion and Conclusion -- References -- Topological Distances Between Brain Networks -- 1 Introduction -- 2 Matrix Norms -- 3 Gromov-Hausdorff Distance -- 4 Kolmogorov-Smirnov Distance -- 5 Comparisons -- 6 Application -- 7 Discussion -- References -- Author Index. |
| Record Nr. | UNINA-9910483163803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Patch-Based Techniques in Medical Imaging [[electronic resource] ] : 4th International Workshop, Patch-MI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings / / edited by Wenjia Bai, Gerard Sanroma, Guorong Wu, Brent C. Munsell, Yiqiang Zhan, Pierrick Coupé
| Patch-Based Techniques in Medical Imaging [[electronic resource] ] : 4th International Workshop, Patch-MI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings / / edited by Wenjia Bai, Gerard Sanroma, Guorong Wu, Brent C. Munsell, Yiqiang Zhan, Pierrick Coupé |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (X, 145 p. 53 illus.) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Health informatics Artificial intelligence Computers Image Processing and Computer Vision Health Informatics Artificial Intelligence Information Systems and Communication Service |
| ISBN | 3-030-00500-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Image Denoising -- Image Registration and Matching -- Image Classification and Detection -- Brain Image Analysis -- Retinal Image Analysis. |
| Record Nr. | UNISA-996466331003316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Patch-Based Techniques in Medical Imaging : 4th International Workshop, Patch-MI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings / / edited by Wenjia Bai, Gerard Sanroma, Guorong Wu, Brent C. Munsell, Yiqiang Zhan, Pierrick Coupé
| Patch-Based Techniques in Medical Imaging : 4th International Workshop, Patch-MI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings / / edited by Wenjia Bai, Gerard Sanroma, Guorong Wu, Brent C. Munsell, Yiqiang Zhan, Pierrick Coupé |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (X, 145 p. 53 illus.) |
| Disciplina |
616.07540285
616.0757 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Health informatics Artificial intelligence Computers Image Processing and Computer Vision Health Informatics Artificial Intelligence Information Systems and Communication Service |
| ISBN | 3-030-00500-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Image Denoising -- Image Registration and Matching -- Image Classification and Detection -- Brain Image Analysis -- Retinal Image Analysis. |
| Record Nr. | UNINA-9910349403603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Patch-Based Techniques in Medical Imaging [[electronic resource] ] : Third International Workshop, Patch-MI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Proceedings / / edited by Guorong Wu, Brent C. Munsell, Yiqiang Zhan, Wenjia Bai, Gerard Sanroma, Pierrick Coupé
| Patch-Based Techniques in Medical Imaging [[electronic resource] ] : Third International Workshop, Patch-MI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Proceedings / / edited by Guorong Wu, Brent C. Munsell, Yiqiang Zhan, Wenjia Bai, Gerard Sanroma, Pierrick Coupé |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XI, 168 p. 59 illus.) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Health informatics Artificial intelligence Arithmetic and logic units, Computer Mathematical statistics Image Processing and Computer Vision Health Informatics Artificial Intelligence Arithmetic and Logic Structures Probability and Statistics in Computer Science |
| ISBN | 3-319-67434-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Multi-atlas segmentation -- Segmentation -- Alzheimer’s disease -- Reconstruction, denoising, super-resolution -- Tumor, lesion -- Classification, retrival. |
| Record Nr. | UNISA-996465914803316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Patch-Based Techniques in Medical Imaging : Third International Workshop, Patch-MI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Proceedings / / edited by Guorong Wu, Brent C. Munsell, Yiqiang Zhan, Wenjia Bai, Gerard Sanroma, Pierrick Coupé
| Patch-Based Techniques in Medical Imaging : Third International Workshop, Patch-MI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Proceedings / / edited by Guorong Wu, Brent C. Munsell, Yiqiang Zhan, Wenjia Bai, Gerard Sanroma, Pierrick Coupé |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XI, 168 p. 59 illus.) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Health informatics Artificial intelligence Arithmetic and logic units, Computer Mathematical statistics Image Processing and Computer Vision Health Informatics Artificial Intelligence Arithmetic and Logic Structures Probability and Statistics in Computer Science |
| ISBN | 3-319-67434-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Multi-atlas segmentation -- Segmentation -- Alzheimer’s disease -- Reconstruction, denoising, super-resolution -- Tumor, lesion -- Classification, retrival. |
| Record Nr. | UNINA-9910484620203321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Patch-Based Techniques in Medical Imaging [[electronic resource] ] : Second International Workshop, Patch-MI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings / / edited by Guorong Wu, Pierrick Coupé, Yiqiang Zhan, Brent C. Munsell, Daniel Rueckert
| Patch-Based Techniques in Medical Imaging [[electronic resource] ] : Second International Workshop, Patch-MI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings / / edited by Guorong Wu, Pierrick Coupé, Yiqiang Zhan, Brent C. Munsell, Daniel Rueckert |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (X, 141 p. 45 illus.) |
| Disciplina | 004 |
| 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 | 3-319-47118-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Automatic Segmentation of Hippocampus for Longitudinal Infant Brain MR Image Sequence by Spatial-Temporal Hypergraph Learning -- Construction of Neonatal Diffusion Atlases via Spatio-Angular Consistency -- Selective Labeling: identifying representative sub-volumes for interactive segmentation -- Robust and Accurate Appearance Models based on Joint Dictionary Learning: Data from the Osteoarthritis Initiative -- Consistent multi-atlas hippocampus segmentation for longitudinal MR brain images with temporal sparse representation -- Sparse-Based Morphometry: Principle and Application to Alzheimer’s Disease -- Multi-Atlas Based Segmentation of Brainstem Nuclei from MR Images by Deep Hyper-Graph Learning -- Patch-Based Discrete Registration of Clinical Brain Images -- Non-local MRI Library-based Super-resolution: Application to Hippocampus Subfield Segmentation -- Patch-based DTI grading: Application to Alzheimer's disease classification -- Hierarchical Multi-Atlas Segmentation using Label-Specific Embeddings, Target-Specific Templates and Patch Refinement -- HIST: HyperIntensity Segmentation Tool -- Supervoxel-Based Hierarchical Markov Random Field Framework for Multi-Atlas Segmentation -- CapAIBL: Automated reporting of cortical PET quantification without need of MRI on brain surface using a patch-based method -- High resolution hippocampus subfield segmentation using multispectral multi-atlas patch-based label fusion -- Identification of water and fat images in Dixon MRI using aggregated patch-based convolutional neural networks -- Estimating Lung Respiratory Motion Using Combined Global and Local Statistical Models. |
| Record Nr. | UNISA-996465552403316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Patch-Based Techniques in Medical Imaging : Second International Workshop, Patch-MI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings / / edited by Guorong Wu, Pierrick Coupé, Yiqiang Zhan, Brent C. Munsell, Daniel Rueckert
| Patch-Based Techniques in Medical Imaging : Second International Workshop, Patch-MI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings / / edited by Guorong Wu, Pierrick Coupé, Yiqiang Zhan, Brent C. Munsell, Daniel Rueckert |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (X, 141 p. 45 illus.) |
| Disciplina | 004 |
| 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 | 3-319-47118-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Automatic Segmentation of Hippocampus for Longitudinal Infant Brain MR Image Sequence by Spatial-Temporal Hypergraph Learning -- Construction of Neonatal Diffusion Atlases via Spatio-Angular Consistency -- Selective Labeling: identifying representative sub-volumes for interactive segmentation -- Robust and Accurate Appearance Models based on Joint Dictionary Learning: Data from the Osteoarthritis Initiative -- Consistent multi-atlas hippocampus segmentation for longitudinal MR brain images with temporal sparse representation -- Sparse-Based Morphometry: Principle and Application to Alzheimer’s Disease -- Multi-Atlas Based Segmentation of Brainstem Nuclei from MR Images by Deep Hyper-Graph Learning -- Patch-Based Discrete Registration of Clinical Brain Images -- Non-local MRI Library-based Super-resolution: Application to Hippocampus Subfield Segmentation -- Patch-based DTI grading: Application to Alzheimer's disease classification -- Hierarchical Multi-Atlas Segmentation using Label-Specific Embeddings, Target-Specific Templates and Patch Refinement -- HIST: HyperIntensity Segmentation Tool -- Supervoxel-Based Hierarchical Markov Random Field Framework for Multi-Atlas Segmentation -- CapAIBL: Automated reporting of cortical PET quantification without need of MRI on brain surface using a patch-based method -- High resolution hippocampus subfield segmentation using multispectral multi-atlas patch-based label fusion -- Identification of water and fat images in Dixon MRI using aggregated patch-based convolutional neural networks -- Estimating Lung Respiratory Motion Using Combined Global and Local Statistical Models. |
| Record Nr. | UNINA-9910483937503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||