Medical Image Computing and Computer Assisted Intervention - MICCAI 2019 : 22nd International Conference, Shenzhen, China, October 13-17, 2019, Proceedings, Part II / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan.

Format:

Book

Contributor:

Shen, Dinggang, Editor.

Liu, Tianming, Editor.

Peters, Terry M., Editor.

Staib, Lawrence H., Editor.

Essert, Caroline, Editor.

Zhou, Xiangyun Sean, Editor.

Yap, Pew-Thian, Editor.

Khan, Ali., Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 11765

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11765

Language:

English

Subjects (All):

Computer vision.

Pattern recognition systems.

Artificial intelligence.

Medical informatics.

Computer Vision.

Automated Pattern Recognition.

Artificial Intelligence.

Health Informatics.

Local Subjects:

Computer Vision.

Automated Pattern Recognition.

Artificial Intelligence.

Health Informatics.

Physical Description:

1 online resource (XXXVI, 874 pages) : 347 illustrations, 312 illustrations in color.

Edition:

1st ed. 2019.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2019.

System Details:

text file PDF

Summary:

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 were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy. Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression. Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging. Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis. Part V: computer assisted interventions; MIC meets CAI. Part VI: computed tomography; X-ray imaging.

Contents:

Image Segmentation

Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation

Comparative Evaluation of Hand-Engineered and Deep-Learned Features for Neonatal Hip Bone Segmentation in Ultrasound

Unsupervised Quality Control of Image Segmentation based on Bayesian Learning

One Network To Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation

'Project and Excite' Modules for Segmentation of Volumetric Medical Scans

Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentation

Learning Cross-Modal Deep Representations for Multi-Modal MR Image Segmentation

Extreme Points Derived Confidence Map as a Cue For Class-Agnostic Segmentation Using Deep Neural Network

Hetero-Modal Variational Encoder-Decoder for Joint Modality Completion and Segmentation

Instance Segmentation from Volumetric Biomedical Images without Voxel-Wise Labeling

Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory and Practice

Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation

HD-Net: Hybrid Discriminative Network for Prostate Segmentation in MR Images

PHiSeg: Capturing Uncertainty in Medical Image Segmentation

Neural Style Transfer Improves 3D Cardiovascular MR Image Segmentation on Inconsistent Data

Supervised Uncertainty Quantification for Segmentation with Multiple Annotations

3D Tiled Convolution for Effective Segmentation of Volumetric Medical Images

Hyper-Pairing Network for Multi-Phase Pancreatic Ductal Adenocarcinoma Segmentation

Statistical intensity- and shape-modeling to automate cerebrovascular segmentation from TOF-MRA data

Segmentation of Vessels in Ultra High Frequency Ultrasound Sequences using Contextual Memory

Accurate Esophageal Gross Tumor Volume Segmentation in PET/CT using Two-Stream Chained 3D Deep Network Fusion

Mixed-Supervised Dual-Network for Medical Image 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.

Other Format:

Printed edition:

ISBN:

978-3-030-32245-8

9783030322458

Access Restriction:

Restricted for use by site license.