Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part VII
The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually d...
| Other Authors: | , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2020, 2020
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| Edition: | 1st ed. 2020 |
| Series: | Image Processing, Computer Vision, Pattern Recognition, and Graphics
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Tractogram filtering of anatomically non-plausible fibers with geometric deep learning
- Unsupervised Deep Learning for Susceptibility Distortion Correction in Connectome Imaging
- Hierarchical geodesic modeling on the diffusion orientation distribution function for longitudinal DW-MRI analysis
- TRAKO: Efficient Transmission of Tractography Data for Visualization
- Spatial Semantic-Preserving Latent Space Learning for Accelerated DWI Diagnostic Report Generation
- Trajectories from Distribution-valued Functional Curves: A Unified Wasserstein Framework
- Characterizing Intra-Soma Diffusion with Spherical Mean Spectrum Imaging
- Functional Brain Networks
- Estimating Common Harmonic Waves of Brain Networks on Stiefel Manifold
- Neural Architecture Search for Optimization of Spatial-temporal Brain Network Decomposition
- Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer’s Disease Analysis
- Discovering Functional Brain Networks with 3D Residual Autoencoder (ResAE)
- Spatiotemporal Attention Autoencoder (STAAE) for ADHD Classification
- Global Diffeomorphic Phase Alignment of Time-series from Resting-state fMRI Data
- Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis
- A shared neural encoding model for the prediction of subject-specific fMRI response
- Neuroimaging
- Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain Graph
- Edge-variational Graph Convolutional Networks for Uncertainty-aware Disease Prediction
- Fisher-Rao Regularized Transport Analysis of the Glymphatic System and Waste Drainage
- Joint Neuroimage Synthesis and Representation Learning for Conversion Prediction of Subjective Cognitive Decline
- Differentiable Deconvolution for Improved Stroke Perfusion Analysis
- Automated Acquisition Planning for Magnetic Resonance Spectroscopy in Brain Cancer
- Positron Emission Tomography
- Simultaneous Denoising and Motion Estimation for Low-dose Gated PET using a Siamese Adversarial Network with Gate-to-Gate Consistency Learning
- Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-based Gating using 3D CT/PET Imaging in Radiotherapy
- Multi-Modality Information Fusionfor Radiomics-based Neural Architecture Search
- Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network
- Rethinking PET Image Reconstruction: Ultra-Low-Dose, Sinogram and Deep Learning
- Clinically Translatable Direct Patlak Reconstruction from Dynamic PET with Motion Correction Using Convolutional Neural Network
- Collimatorless Scintigraphy for Imaging Extremely Low Activity Targeted Alpha Therapy (TAT) with Weighted Robust Least Square (WRLS)
- Disentangled Intensive Triplet Autoencoder for Infant Functional Connectome Fingerprinting
- COVLET: Covariance-based Wavelet-like Transform for Statistical Analysis of Brain Characteristics in Children
- Species-Shared and -Specific Structural Connections Revealed by Dirty Multi-Task Regression
- Self-weighted Multi-Task Learning for Subjective Cognitive Decline Diagnosis
- Unified Brain Network with Functional and Structural Data
- Integrating Similarity Awareness and Adaptive Calibration in Graph Convolution Network to Predict Disease
- Infant Cognitive Scores Prediction With Multi-stream Attention-based Temporal Path Signature Features
- Masked Multi-Task Network for Case-level Intracranial Hemorrhage Classification in Brain CT Volumes
- Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates
- Supervised Multi-topology Network Cross-diffusion for Population-Driven Brain Network Atlas Estimation
- Spatial Similarity-Aware Learning and Fused Deep Polynomial Network for Detection of Obsessive-Compulsive Disorder
- Deep Representation Learning For Multimodal Brain Networks
- Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis
- Patch-based abnormality maps for improved deep learning-based classification of Huntington's disease
- A Deep Spatial Context Guided Framework for Infant Brain Subcortical Segmentation
- Modelling the Distribution of 3D Brain MRI using a 2D Slice VAE
- Spatial Component Analysis to Mitigate Multiple Testing in Voxel-Based Analysis
- MAGIC: Multi-scale Heterogeneity Analysis and Clustering for Brain Diseases
- PIANO: Perfusion Imaging via Advection-diffusion
- Hierarchical Bayesian Regression for Multi-Site Normative Modeling of Neuroimaging Data
- Image-level Harmonization of Multi-Site Data using Image-and-Spatial Transformer Networks
- A Disentangled Latent Space for Cross-Site MRI Harmonization
- Brain Development and Atlases
- A New Metric for Characterizing Dynamic Redundancy of Dense Brain Chronnectome and Its Application to Early Detection of Alzheimer's Disease
- A computational framework for dissociating development-related from individually variable flexibility in regional modularity assignment in early infancy
- Domain-invariant Prior Knowledge Guided Attention Networks for Robust Skull Stripping of Developing Macaque Brains
- Parkinson's Disease Detection from fMRI-derived Brainstem Regional Functional Connectivity Networks
- Persistent Feature Analysis of Multimodal Brain Networks Using Generalized Fused Lasso for EMCI Identification
- Recovering Brain Structural Connectivity from Functional Connectivity via Multi-GCN based Generative Adversarial Network
- From Connectomic to Task-evoked Fingerprints: Individualized Prediction of Task Contrasts from Resting-state Functional Connectivity
- Enriched Representation Learning in Resting-State fMRI for Early MCI Diagnosis
- Whole MILC: generalizing learned dynamics across tasks, datasets, and populations
- A physics-informed geometric learning model for pathological tau spread in Alzheimer's disease
- A deep pattern recognition approach for inferring respiratory volume fluctuations from fMRI data
- A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism
- Poincare embedding reveals edge-based functional networks of the brain
- The constrained network-based statistic: a new level of inference for neuroimaging
- Learning Personal Representations from fMRIby Predicting Neurofeedback Performance
- A 3D Convolutional Encapsulated Long Short-Term Memory (3DConv-LSTM) Model for Denoising fMRI Data
- Detecting Changes of Functional Connectivity by Dynamic Graph Embedding Learning
- Partial Volume Segmentation of Brain MRI Scans of any Resolution and Contrast
- BDB-Net: Boundary-enhanced DualBranch Network for Whole Brain Segmentation
- Brain Age Estimation From MRI Using a Two-Stage Cascade Network with a Ranking Loss
- Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation
- Optimizing Visual Cortex Parameterization with Error-Tolerant Teichmüller Map in Retinotopic Mapping
- Multi-Scale Enhanced Graph Convolutional Network for Early Mild Cognitive Impairment Detection
- Construction of Spatiotemporal Infant Cortical Surface Functional Templates
- DWI and Tractography
- Tract Dictionary Learning for Fast and Robust Recognition of Fiber Bundles
- Globally Optimized Super-Resolution of Diffusion MRI Data via Fiber Continuity
- White Matter Tract Segmentation with Self-supervised Learning
- Estimating Tissue Microstructure with Undersampled Diffusion Data via Graph Convolutional Neural Networks