Medical Image Computing and Computer Assisted Intervention - MICCAI 2019

Segmentation.- Fully Automated Pancreas Segmentation with Two-stage 3D Convolutional Neural Networks.- Globally Guided Progressive Fusion Network for 3D Pancreas Segmentation.- Automatic Segmentation of Muscle Tissue and Inter-muscular Fat in Thigh and Calf MRI Images.- Resource Optimized Neural Architecture Search for 3D Medical Image Segmentation.- Radiomics-guided GAN for Segmentation of Liver Tumor without Contrast Agents.- Liver Segmentation in Magnetic Resonance Imaging via Mean Shape Fitting with Fully Convolutional Neural Networks.- Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation.- Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss.- Learning Shape Representation on Sparse Point Clouds for Volumetric Image Segmentation.- Collaborative Multi-agent Learning for MR Knee Articular Cartilage Segmentation.- 3D U2-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation.- Impact of Adversarial Examples on Deep Learning Segmentation Models.- Multi-Resolution Path CNN with Deep Supervision for Intervertebral Disc Localization and Segmentation.- Automatic paraspinal muscle segmentation in patients with lumbar pathology using deep convolutional neural network.- Constrained Domain Adaptation for Segmentation.- Image Registration.-Image-and-Spatial Transformer Networks for Structure-Guided Image Registration.- Probabilistic Multilayer Regularization Network for Unsupervised 3D Brain Image Registration.- A deep learning approach to MR-less spatial normalization for tau PET images.- TopAwaRe: Topology-Aware Registration.- Multimodal Data Registration for Brain Structural Association Networks.- Dual-Stream Pyramid Registration Network.- A Cooperative Autoencoder for Population-Based Regularization of CNN Image Registration.- Conditional Segmentation in Lieu of Image Registration.- On the applicability of registration uncertainty.- DeepAtlas: Joint Semi-Supervised Learning of Image Registration and Segmentation.- Linear Time Invariant Model based Motion Correction (LiMo-Moco) of Dynamic Radial Contrast Enhanced MRI.- Incompressible image registration using divergence-conforming B-splines.- Cardiovascular Imaging.- Direct Quantification for Coronary Artery Stenosis Using Multiview Learning.- Bayesian Optimization on Large Graphs via a Graph Convolutional Generative Model: Application in Cardiac Model Personalization.- Discriminative Coronary Artery Tracking via 3D CNN in Cardiac CT Angiography.- Multi-modality Whole-Heart and Great Vessel Segmentation in Congenital Heart Disease using Deep Neural Networks and Graph Matching.- Harmonic Balance Techniques in Cardiovascular Fluid Mechanics.- Deep learning within a priori temporal feature spaces for large-scale dynamic MR image reconstruction: Application to 5-D cardiac MR Multitasking.- k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-temporal Correlations.- Model-based reconstruction for highly accelerated first-pass perfusion cardiac MRI.- Learning Shape Priors for Robust Cardiac MR Segmentation from Multi-view images.- Right Ventricle Segmentation in Short-Axis MRI Using A Shape Constrained Dense Connected U-net.- Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction.- A Fine-Grain Error Map Prediction and Segmentation Quality Assessment Framework for Whole-Heart Segmentation.- Cardiac Segmentation from LGE MRI Using Deep Neural Network Incorporating Shape and Spatial Priors.- Curriculum semi-supervised segmentation.- A Multi-modal Network for Cardiomyopathy Death Risk Prediction with CMR Images and Clinical Information.-3D Cardiac Shape Prediction with Deep Neural Networks: Simultaneous Use of Images and Patient Metadata.- Discriminative Consistent Domain Generation for Semi-supervised Learning.- Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation.- MSU-Net: Multiscale Statistical U-Net for Real-time 3D Cardiac MRI Video Segmentation.- The Domain Shift Problem of Medical Image Segmentation and Vendor-Adaptation by Unet-GAN.- Cardiac MRI Segmentation with Strong Anatomical Guarantees.- Decompose-and-Integrate Learning for Multi-class Segmentation in Medical Images.- Missing Slice Imputation in Population CMR Imaging via Conditional Generative Adversarial Nets.- Unsupervised Standard Plane Synthesis in Population Cine MRI via Cycle-Consistent Adversarial Networks.- Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation.- Recurrent Aggregation Learning for Multi-View Echocardiographic Sequences Segmentation.- Echocardiography View Classification Using Quality Transfer Star Generative Adversarial Networks.- Dual-view Joint Estimation of Left Ventricular Ejection Fraction with Uncertainty Modelling in Echocardiograms.- Frame Rate Up-Conversion in Echocardiography Using a Conditioned Variational Autoencoder and Generative Adversarial Model.- Annotation-Free Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images.- DeepAAA: clinically applicable and generalizable detection of abdominal aortic aneurysm using deep learning.- Texture-based classification of significant stenosis in CCTA multi-view images of coronary arteries.- Fourier Spectral Dynamic Data Assimilation: Interlacing CFD with 4D flow MRI.- Quality Control-Driven Image Segmentation Towards Reliable Automatic Image Analysis in Large-Scale Cardiovascular Magnetic Resonance Aortic Cine Imaging.- HFA-Net: 3D Cardiovascular Image Segmentation with Asymmetrical Pooling and Content-Aware Fusion.- Spectral CT based training dataset generation and augmentation for conventional CT vascular segmentation.- Context-Aware Inductive Bias Learning for Vessel Border Detection in Multi-modal Intracoronary Imaging.- Growth, Development, Atrophy and Progression.- Neural parameters estimation for brain tumor growth modeling.- Learning-Guided Infinite Network Atlas Selection for Predicting Longitudinal Brain Network Evolution from a Single Observation.- Deep Probabilistic Modeling of Glioma Growth.- Surface-Volume Consistent Construction of Longitudinal Atlases for the Early Developing Brains.- Variational Autoencoder for Regression: Application to Brain Aging Analysis.- Early Development of Infant Brain Complex Network.- Revealing Developmental Regionalization of Infant Cerebral Cortex Based on Multiple Cortical Properties.- Continually Modeling Alzheimer's Disease Progression via Deep Multi-Order Preserving Weight Consolidation.- Disease Knowledge Transfer across Neurodegenerative Diseases.