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Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

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Cover of 'Medical Image Computing and Computer Assisted Intervention – MICCAI 2020'

Table of Contents

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    Book Overview
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    Chapter 1 A New Metric for Characterizing Dynamic Redundancy of Dense Brain Chronnectome and Its Application to Early Detection of Alzheimer’s Disease
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    Chapter 2 A Computational Framework for Dissociating Development-Related from Individually Variable Flexibility in Regional Modularity Assignment in Early Infancy
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    Chapter 3 Domain-Invariant Prior Knowledge Guided Attention Networks for Robust Skull Stripping of Developing Macaque Brains
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    Chapter 4 Parkinson’s Disease Detection from fMRI-Derived Brainstem Regional Functional Connectivity Networks
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    Chapter 5 Persistent Feature Analysis of Multimodal Brain Networks Using Generalized Fused Lasso for EMCI Identification
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    Chapter 6 Recovering Brain Structural Connectivity from Functional Connectivity via Multi-GCN Based Generative Adversarial Network
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    Chapter 7 From Connectomic to Task-Evoked Fingerprints: Individualized Prediction of Task Contrasts from Resting-State Functional Connectivity
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    Chapter 8 Disentangled Intensive Triplet Autoencoder for Infant Functional Connectome Fingerprinting
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    Chapter 9 COVLET: Covariance-Based Wavelet-Like Transform for Statistical Analysis of Brain Characteristics in Children
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    Chapter 10 Species-Shared and -Specific Structural Connections Revealed by Dirty Multi-task Regression
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    Chapter 11 Self-weighted Multi-task Learning for Subjective Cognitive Decline Diagnosis
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    Chapter 12 Unified Brain Network with Functional and Structural Data
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    Chapter 13 Integrating Similarity Awareness and Adaptive Calibration in Graph Convolution Network to Predict Disease
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    Chapter 14 Infant Cognitive Scores Prediction with Multi-stream Attention-Based Temporal Path Signature Features
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    Chapter 15 Masked Multi-Task Network for Case-Level Intracranial Hemorrhage Classification in Brain CT Volumes
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    Chapter 16 Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates
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    Chapter 17 Supervised Multi-topology Network Cross-Diffusion for Population-Driven Brain Network Atlas Estimation
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    Chapter 18 Partial Volume Segmentation of Brain MRI Scans of Any Resolution and Contrast
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    Chapter 19 BDB-Net: Boundary-Enhanced Dual Branch Network for Whole Brain Segmentation
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    Chapter 20 Brain Age Estimation from MRI Using a Two-Stage Cascade Network with Ranking Loss
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    Chapter 21 Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation
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    Chapter 22 Optimizing Visual Cortex Parameterization with Error-Tolerant Teichmüller Map in Retinotopic Mapping
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    Chapter 23 Multi-scale Enhanced Graph Convolutional Network for Early Mild Cognitive Impairment Detection
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    Chapter 24 Construction of Spatiotemporal Infant Cortical Surface Functional Templates
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    Chapter 25 Tract Dictionary Learning for Fast and Robust Recognition of Fiber Bundles
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    Chapter 26 Globally Optimized Super-Resolution of Diffusion MRI Data via Fiber Continuity
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    Chapter 27 White Matter Tract Segmentation with Self-supervised Learning
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    Chapter 28 Estimating Tissue Microstructure with Undersampled Diffusion Data via Graph Convolutional Neural Networks
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    Chapter 29 Tractogram Filtering of Anatomically Non-plausible Fibers with Geometric Deep Learning
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    Chapter 30 Unsupervised Deep Learning for Susceptibility Distortion Correction in Connectome Imaging
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    Chapter 31 Hierarchical Geodesic Modeling on the Diffusion Orientation Distribution Function for Longitudinal DW-MRI Analysis
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    Chapter 32 TRAKO: Efficient Transmission of Tractography Data for Visualization
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    Chapter 33 Spatial Semantic-Preserving Latent Space Learning for Accelerated DWI Diagnostic Report Generation
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    Chapter 34 Trajectories from Distribution-Valued Functional Curves: A Unified Wasserstein Framework
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    Chapter 35 Characterizing Intra-soma Diffusion with Spherical Mean Spectrum Imaging
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    Chapter 36 Estimating Common Harmonic Waves of Brain Networks on Stiefel Manifold
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    Chapter 37 Neural Architecture Search for Optimization of Spatial-Temporal Brain Network Decomposition
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    Chapter 38 Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer’s Disease Analysis
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    Chapter 39 Enriched Representation Learning in Resting-State fMRI for Early MCI Diagnosis
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    Chapter 40 Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations
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    Chapter 41 A Physics-Informed Geometric Learning Model for Pathological Tau Spread in Alzheimer’s Disease
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    Chapter 42 A Deep Pattern Recognition Approach for Inferring Respiratory Volume Fluctuations from fMRI Data
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    Chapter 43 A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism
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    Chapter 44 Poincaré Embedding Reveals Edge-Based Functional Networks of the Brain
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    Chapter 45 The Constrained Network-Based Statistic: A New Level of Inference for Neuroimaging
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    Chapter 46 Learning Personal Representations from fMRI by Predicting Neurofeedback Performance
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    Chapter 47 A 3D Convolutional Encapsulated Long Short-Term Memory (3DConv-LSTM) Model for Denoising fMRI Data
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    Chapter 48 Detecting Changes of Functional Connectivity by Dynamic Graph Embedding Learning
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    Chapter 49 Discovering Functional Brain Networks with 3D Residual Autoencoder (ResAE)
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    Chapter 50 Spatiotemporal Attention Autoencoder (STAAE) for ADHD Classification
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    Chapter 51 Global Diffeomorphic Phase Alignment of Time-Series from Resting-State fMRI Data
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    Chapter 52 Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis
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    Chapter 53 A Shared Neural Encoding Model for the Prediction of Subject-Specific fMRI Response
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    Chapter 54 Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain Graph
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    Chapter 55 Edge-Variational Graph Convolutional Networks for Uncertainty-Aware Disease Prediction
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    Chapter 56 Fisher-Rao Regularized Transport Analysis of the Glymphatic System and Waste Drainage
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    Chapter 57 Joint Neuroimage Synthesis and Representation Learning for Conversion Prediction of Subjective Cognitive Decline
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    Chapter 58 Differentiable Deconvolution for Improved Stroke Perfusion Analysis
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    Chapter 59 Spatial Similarity-Aware Learning and Fused Deep Polynomial Network for Detection of Obsessive-Compulsive Disorder
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    Chapter 60 Deep Representation Learning for Multimodal Brain Networks
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    Chapter 61 Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis
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    Chapter 62 Patch-Based Abnormality Maps for Improved Deep Learning-Based Classification of Huntington’s Disease
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    Chapter 63 A Deep Spatial Context Guided Framework for Infant Brain Subcortical Segmentation
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    Chapter 64 Modelling the Distribution of 3D Brain MRI Using a 2D Slice VAE
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    Chapter 65 Spatial Component Analysis to Mitigate Multiple Testing in Voxel-Based Analysis
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    Chapter 66 MAGIC: Multi-scale Heterogeneity Analysis and Clustering for Brain Diseases
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    Chapter 67 PIANO: Perfusion Imaging via Advection-Diffusion
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    Chapter 68 Hierarchical Bayesian Regression for Multi-site Normative Modeling of Neuroimaging Data
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    Chapter 69 Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks
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    Chapter 70 A Disentangled Latent Space for Cross-Site MRI Harmonization
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    Chapter 71 Automated Acquisition Planning for Magnetic Resonance Spectroscopy in Brain Cancer
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    Chapter 72 Simultaneous Denoising and Motion Estimation for Low-Dose Gated PET Using a Siamese Adversarial Network with Gate-to-Gate Consistency Learning
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    Chapter 73 Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-Based Gating Using 3D CT/PET Imaging in Radiotherapy
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    Chapter 74 Multi-modality Information Fusion for Radiomics-Based Neural Architecture Search
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    Chapter 75 Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network
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    Chapter 76 Rethinking PET Image Reconstruction: Ultra-Low-Dose, Sinogram and Deep Learning
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    Chapter 77 Clinically Translatable Direct Patlak Reconstruction from Dynamic PET with Motion Correction Using Convolutional Neural Network
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    Chapter 78 Collimatorless Scintigraphy for Imaging Extremely Low Activity Targeted Alpha Therapy (TAT) with Weighted Robust Least Squares (WRLS)
Attention for Chapter 58: Differentiable Deconvolution for Improved Stroke Perfusion Analysis
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Chapter title
Differentiable Deconvolution for Improved Stroke Perfusion Analysis
Chapter number 58
Book title
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
Published in
arXiv, September 2020
DOI 10.1007/978-3-030-59728-3_58
Book ISBNs
978-3-03-059727-6, 978-3-03-059728-3

Ezequiel de la Rosa, David Robben, Diana M. Sima, Jan S. Kirschke, Bjoern Menze, de la Rosa, Ezequiel, Robben, David, Sima, Diana M., Kirschke, Jan S., Menze, Bjoern

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 29%
Student > Master 3 18%
Student > Bachelor 2 12%
Student > Ph. D. Student 2 12%
Student > Doctoral Student 1 6%
Other 1 6%
Unknown 3 18%
Readers by discipline Count As %
Computer Science 5 29%
Engineering 4 24%
Unspecified 1 6%
Agricultural and Biological Sciences 1 6%
Business, Management and Accounting 1 6%
Other 2 12%
Unknown 3 18%

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