Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part III /
The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019. The 539 revised full papers presented w...
| Corporate Author: | |
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| Other Authors: | , , , , , , , |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2019.
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| Edition: | 1st ed. 2019. |
| Series: | Image Processing, Computer Vision, Pattern Recognition, and Graphics ;
11766 |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-030-32248-9 |
Table of Contents:
- Neuroimage Reconstruction and Synthesis
- Isotropic MRI Super-Resolution Reconstruction with Multi-Scale Gradient Field Prior
- A Two-Stage Multi-Loss Super-Resolution Network For Arterial Spin Labeling Magnetic Resonance Imaging
- Model Learning: Primal Dual Networks for Fast MR imaging
- Model-based Convolutional De-Aliasing Network Learning for Parallel MR Imaging
- Joint Reconstruction of PET + Parallel-MRI in a Bayesian Coupled-Dictionary MRF Framework
- Deep Learning Based Framework for Direct Reconstruction of PET Images
- Nonuniform Variational Network: Deep Learning for Accelerated Nonuniform MR Image Reconstruction
- Reconstruction of Isotropic High-Resolution MR Image from Multiple Anisotropic Scans using Sparse Fidelity Loss and Adversarial Regularization
- Single Image Based Reconstruction of High Field-like MR Images
- Deep Neural Network for QSM Background Field Removal
- RinQ Fingerprinting: Recurrence-informed Quantile Networks for Magnetic Resonance Fingerprinting
- RCA-U-Net: Residual Channel Attention U-Net for Fast Tissue Quantification in Magnetic Resonance Fingerprinting
- GANReDL: Medical Image enhancement using a generative adversarial network with real-order derivative induced loss functions
- Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Networks
- Semi-Supervised VAE-GAN for Out-of-Sample Detection Applied to MRI Quality Control
- Disease-Image Specific Generative Adversarial Network for Brain Disease Diagnosis with Incomplete Multi-Modal Neuroimages
- Predicting the Evolution of White Matter Hyperintensities in Brain MRI using Generative Adversarial Networks and Irregularity Map
- CoCa-GAN: Common-feature-learning-based Context-aware Generative Adversarial Network for Glioma Grading
- Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression
- Neuroimage Segmentation
- Scribble-based Hierarchical Weakly Supervised Learning for Brain Tumor Segmentation
- 3D Dilated Multi-Fiber Network for Real-time Brain Tumor Segmentation in MRI
- Refined-Segmentation R-CNN: A Two-stage Convolutional Neural Network for Punctate White Matter Lesion Segmentation in Preterm Infants
- VoteNet: A Deep Learning Label Fusion Method for Multi-Atlas Segmentation
- Weakly Supervised Brain Lesion Segmentation via Attentional Representation Learning
- Scalable Neural Architecture Search for 3D Medical Image Segmentation
- Unified Attentional Generative Adversarial Network for Brain Tumor Segmentation From Multimodal Unpaired Images
- High Resolution Medical Image Segmentation using Data-swapping Method
- X-Net: Brain Stroke Lesion Segmentation Based on Depthwise Separable Convolution and Long-range Dependencies
- Multi-View Semi-supervised 3D Whole Brain Segmentation with a Self-Ensemble Network
- CLCI-Net: Cross-Level Fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke
- Brain Segmentation from k-space with End-to-end Recurrent Attention Network
- Spatial Warping Network for 3D Segmentation of the Hippocampus in MR Images
- CompareNet: Anatomical Segmentation Network with Deep Non-local Label Fusion
- A Joint 3D+2D Fully Convolutional Framework for Subcortical Segmentation
- U-ReSNet: Ultimate coupling of Registration and Segmentation with deep Nets
- Generative adversarial network for segmentation of motion affected neonatal brain MRI
- Interactive deep editing framework for medical image segmentation
- Multiple Sclerosis Lesion Segmentation with Tiramisu and 2.5D Stacked Slices
- Improving Multi-Atlas Segmentation by Convolutional Neural Network Based Patch Error Estimation
- Unsupervised deep learning for Bayesian brain MRI segmentation
- Online atlasing using an iterative centroid
- ARS-Net: Adaptively Rectified Supervision Network for Automated 3D Ultrasound Image Segmentation
- Complete Fetal Head Compounding from Multi-View 3D Ultrasound
- SegNAS3D: Network Architecture Search with Derivative-Free Global Optimization for 3D Image Segmentation
- Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation
- RSANet: Recurrent Slice-wise Attention Network for Multiple Sclerosis Lesion Segmentation
- Deep Cascaded Attention Networks for Multi-task Brain Tumor Segmentation
- Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation
- 3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation
- Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated Fusion
- Multi-task Attention-based Semi-supervised Learning for Medical Image Segmentation
- AssemblyNet: A Novel Deep Decision-Making Process for Whole Brain MRI Segmentation
- Automated Parcellation of the Cortex using Structural Connectome Harmonics
- Hierarchical parcellation of the cerebellum
- Intrinsic Patch-based Cortical Anatomical Parcellation using Graph Convolutional Neural Network on Surface Manifold
- Cortical Surface Parcellation using Spherical Convolutional Neural Networks
- A Soft STAPLE Algorithm Combined with Anatomical Knowledge
- Diffusion Weighted Magnetic Resonance Imaging
- Multi-Stage Image Quality Assessment of Diffusion MRI via Semi-Supervised Nonlocal Residual Networks
- Reconstructing High-Quality Diffusion MRI Data from Orthogonal Slice-Undersampled Data Using Graph Convolutional Neural Networks
- Surface-based Tracking of U-fibers in the Superficial White Matter
- Probing Brain Micro-Architecture by Orientation Distribution Invariant Identification of Diffusion Compartments
- Characterizing Non-Gaussian Diffusion in Heterogeneously Oriented Tissue Microenvironments
- Topographic Filtering of Tractograms as Vector Field Flows
- Enabling Multi-Shell b-Value Generalizability of Data-Driven Diffusion Models with Deep SHORE
- Super-Resolved q-Space Deep Learning
- Joint Identification of Network Hub Nodes by Multivariate Graph Inference
- Deep white matter analysis: fast, consistent tractography segmentation across populations and dMRI acquisitions
- Improved Placental Parameter Estimation Using Data-Driven Bayesian Modelling
- Optimal experimental design for biophysical modelling in multidimensional diffusion MRI
- DeepTract: A Probabilistic Deep Learning Framework for White Matter Fiber Tractography
- Fast and Scalable Optimal Transport for Brain Tractograms
- A hybrid deep learning framework for integrated segmentation and registration: evaluation on longitudinal white matter tract changes
- Constructing Consistent Longitudinal Brain Networks by Group-wise Graph Learning
- Functional Neuroimaging (fMRI)
- Multi-layer temporal network analysis reveals increasing temporal reachability and spreadability in the first two years of life
- A matched filter decomposition of fMRI into resting and task components
- Identification of Abnormal Circuit Dynamics in Major Depressive Disorder via Multiscale Neural Modeling of Resting-state fMRI
- Integrating Functional and Structural Connectivities via Diffusion-Convolution-Bilinear Neural Network
- Invertible Network for Classification and Biomarker Selection for ASD
- Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data
- Revealing Functional Connectivity by Learning Graph Laplacian
- Constructing Multi-Scale Connectome Atlas by Learning Common Topology of Brain Networks
- Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale
- Identify Hierarchical Structures from Task-based fMRI Data via Hybrid Spatiotemporal Neural Architecture Search Net
- A Deep Learning Framework for Noise Component Detection from Resting-state Functional MRI
- A Novel Graph Wavelet Model for Brain Multi-Scale Functional-structural Feature Fusion
- Combining Multiple Behavioral Measures and Multiple Connectomes via Multiway Canonical Correlation Analysis
- Decoding brain functional connectivity implicated in AD and MCI
- Interpretable Feature Learning Using Multi-Output Takagi-Sugeno-Kang Fuzzy System for Multi-center ASD Diagnosis
- Interpretable Multimodality Embedding Of Cerebral Cortex Using Attention Graph Network For Identifying Bipolar Disorder
- Miscellaneous Neuroimaging
- Doubly Weak Supervision of Deep Learning Models for Head CT
- Detecting Acute Strokes from Non-Contrast CT Scan Data Using Deep Convolutional Neural Networks
- FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images
- Regression-based Line Detection Network for Delineation of Largely Deformed Brain Midline
- Siamese U-Net with Healthy Template for Accurate Segmentation of Intracranial Hemorrhage
- Automated Infarct Segmentation from Follow-up Non-Contrast CT Scans in Patients with Acute Ischemic Stroke Using Dense Multi-Path Contextual Generative Adversarial Network
- Recurrent sub-volume analysis of head CT scans for the detection of intracranial hemorrhage
- Cephalometric Landmark Detection by Attentive Feature Pyramid Fusion and Regression-Voting.