Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 : 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part VII / edited by Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz.

Format:

Book

Contributor:

Martel, Anne L., Editor.

Abolmaesumi, Purang, Editor.

Stoyanov, Danail, Editor.

Mateus, Diana., Editor.

Zuluaga, Maria A., Editor.

Zhou, S. Kevin, Editor.

Racoceanu, Daniel, Editor.

Joskowicz, Leo., Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 12267

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12267

Language:

English

Subjects (All):

Computer vision.

Artificial intelligence.

Social sciences-Data processing.

Education-Data processing.

Computer Vision.

Artificial Intelligence.

Computer Application in Social and Behavioral Sciences.

Computers and Education.

Local Subjects:

Computer Vision.

Artificial Intelligence.

Computer Application in Social and Behavioral Sciences.

Computers and Education.

Physical Description:

1 online resource (XXXVII, 817 pages) : 30 illustrations

Edition:

1st ed. 2020.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2020.

System Details:

text file PDF

Summary:

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 due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis Part IV: segmentation; shape models and landmark detection Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography.

Contents:

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

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

Partial Volume Segmentation of Brain MRI Scans of any Resolution and Contrast

BDB-Net: Boundary-enhanced Dual Branch 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

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

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

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

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

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 Fusion for 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).

Other Format:

Printed edition:

ISBN:

978-3-030-59728-3

9783030597283

Access Restriction:

Restricted for use by site license.