Título :	22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part IV
Tipo de documento:	documento electrónico
Autores:	Shen, Dinggang, ; Liu, Tianming, ; Peters, Terry M., ; Staib, Lawrence H., ; Essert, Caroline, ; Zhou, Sean, ; Yap, Pew-Thian, ; Khan, Ali,
Mención de edición:	1 ed.
Editorial:	[s.l.] : Springer
Fecha de publicación:	2019
Número de páginas:	XXXVIII, 809 p.
ISBN/ISSN/DL:	978-3-030-32251-9
Nota general:	Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Palabras clave:	Visión por computador  Sistemas de reconocimiento de patrones  Inteligencia artificial  Informática Médica  Reconocimiento de patrones automatizado  Informática de la Salud
Índice Dewey:	006.37 Visión artificial
Resumen:	El conjunto de seis volúmenes LNCS 11764, 11765, 11766, 11767, 11768 y 11769 constituye las actas arbitradas de la 22.ª Conferencia Internacional sobre Computación de Imágenes Médicas e Intervención Asistida por Computadora, MICCAI 2019, celebrada en Shenzhen, China, en octubre de 2019. Los 539 artículos completos revisados ​​presentados fueron cuidadosamente revisados ​​y seleccionados entre 1730 presentaciones en un proceso de revisión doble ciego. Los artículos están organizados en las siguientes secciones temáticas: Parte I: imágenes ópticas; endoscopia; microscopía. Parte II: segmentación de imágenes; registro de imagen; imágenes cardiovasculares; crecimiento, desarrollo, atrofia y progresión. Parte III: reconstrucción y síntesis de neuroimágenes; segmentación de neuroimagen; imágenes por resonancia magnética ponderada por difusión; neuroimagen funcional (fMRI); neuroimagen variada. Parte IV: forma; predicción; detección y localización; aprendizaje automático; diagnóstico asistido por ordenador; Reconstrucción y síntesis de imágenes. Parte V: intervenciones asistidas por ordenador; MIC se encuentra con CAI. Parte VI: tomografía computarizada; Imágenes de rayos X.
Nota de contenido:	Shape -- A CNN-Based Framework for Statistical Assessment of Spinal Shape and Curvature in Whole-Body MRI Images of Large Populations -- Exploiting Reliability-guided Aggregation for the Assessment of Curvilinear Structure Tortuosity -- A Surface-theoretic Approach for Statistical Shape Modeling -- Shape Instantiation from A Single 2D Image to 3D Point Cloud with One-stage Learning -- Placental Flattening via Volumetric Parameterization with Dirichlet Energy Regularization -- Fast Polynomial Approximation to Heat Diffusion in Manifolds -- Hierarchical Multi-Geodesic Model for Longitudinal Analysis of Temporal Trajectories of Anatomical Shape and Covariates -- Clustering of longitudinal shape data sets using mixture of separate or branching trajectories -- Group-wise Graph Matching of Cortical Gyral Hinges -- Multi-view Graph Matching of Cortical Landmarks -- Patient-specific Conditional Joint Models of Shape, Image Features and Clinical Indicators -- Surface-Based Spatial Pyramid Matching of Cortical Regions for Analysis of Cognitive Performance -- Prediction -- Diagnosis-guided multi-modal feature selection for prognosis prediction of lung squamous cell carcinoma -- Graph convolution based attention model for personalized disease prediction -- Predicting Early Stages of Neurodegenerative Diseases via Multi-task Low-rank Feature Learning -- Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments Over Progressions -- Deep Granular Feature-Label Distribution Learning for Neuroimaging-based Infant Age Prediction -- End-to-End Dementia Status Prediction from Brain MRI using Multi-Task Weakly-Supervised Attention Network -- Unified Modeling of Imputation, Forecasting, and Prediction for AD Progression -- LSTM Network for Prediction of Hemorrhagic Transformation in Acute Stroke -- Inter-modality Dependence Induced Data Recovery for MCI Conversion Prediction -- Preprocessing, Prediction and Significance: Framework and Application to Brain Imaging -- Early Prediction of Alzheimer's Disease progression using Variational Autoencoder -- Integrating Heterogeneous Brain Networks for Predicting Brain Disease Conditions -- Detection and Localization -- Uncertainty-informed detection of epileptogenic brain malformations using Bayesian neural networks -- Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network -- Intracranial aneurysms detection in 3D cerebrovascular mesh model with ensemble deep learning -- Automated Noninvasive Seizure Detection and Localization Using Switching Markov Models and Convolutional Neural Networks -- Multiple Landmarks Detection using Multi-Agent Reinforcement Learning -- Spatiotemporal Breast Mass Detection Network (MD-Net) in 4D DCE-MRI Images -- Automated Pulmonary Embolism Detection from CTPA Images using an End-to-End Convolutional Neural Network -- Pixel-wise anomaly ratings using Variational Auto-Encoders -- HR-CAM: Precise Localization of pathology using multi-level learning in CNNs -- Novel Iterative Attention Focusing Strategy for Joint Pathology Localization and Diagnosis of MCI Progression -- Automatic Vertebrae Recognition from Arbitrary Spine MRI images by a Hierarchical Self-calibration Detection Framework -- Machine Learning -- Image data validation for medical systems -- Captioning Ultrasound Images Automatically -- Feature Transformers: Privacy Preserving Life Learning Framework for Healthcare Applications -- As easy as 1, 2... 4? Uncertainty in counting tasks for medical imaging -- Generalizable Feature Learning in the Presence of Data Bias and Domain Class Imbalance with Application to Skin Lesion Classification -- Learning task-specific and shared representations in medical imaging -- Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis -- Efficient Ultrasound Image Analysis Models with Sonographer Gaze Assisted Distillation -- Fetal Pose Estimation in Volumetric MRI using 3D Convolution Neural Network -- Multi-Stage Prediction Networks for Data Harmonization -- Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik's Cube -- Bayesian Volumetric Autoregressive generative models for better semisupervised learning with scarce Medical imaging data -- Data Augmentation for Regression Neural Networks -- A Dirty Multi-task Learning Method for Multi-modal Brain Imaging Genetics -- Robust and Discriminative Brain Genome Association Analysis -- Symmetric Dual Adversarial Connectomic Domain Alignment for Predicting Isomorphic Brain Graph From a Baseline Graph -- Harmonization of Infant Cortical Thickness using Surface-to-Surface Cycle-Consistent Adversarial Networks -- Quantifying Confounding Bias in Neuroimaging Datasets with Causal Inference -- Computer-aided Diagnosis -- Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification -- Deep Angular Embedding and Feature Correlation Attention for Breast MRI Cancer Analysis -- Fully Deep Learning for Slit-lamp Photo based NuclearCataract Grading -- Overcoming Data Limitation in Medical Visual Question Answering -- Multi-Instance Multi-Scale CNN for Medical Image Classification -- Improving Uncertainty Estimation in Convolutional Neural Networks Using Inter-rater Agreement -- Improving Skin Condition Classification with a Visual Symptom Checker Trained using Reinforcement Learning -- DScGANS: Integrate Domain Knowledge in Training Dual-Path Semi-Supervised Conditional Generative Adversarial Networks and S3VM for Ultrasonography Thyroid Nodules Classification -- Similarity steered generative adversarial network and adaptive transfer learning for malignancy characterization of hepatocellualr carcinoma -- Unsupervised Clustering of Quantitative Imaging Subtypes using Autoencoder and Gaussian Mixture Model -- Adaptive Sparsity Regularization Based Collaborative Clustering for Cancer Prognosis -- Coronary Artery Plaque Characterization from CCTA Scans using Deep Learning and Radiomics -- Response Estimation through SpatiallyOriented Neural Network and Texture Ensemble (RESONATE) -- STructural Rectal Atlas Deformation (StRAD) features for characterizing intra- and peri-wall chemoradiation response on MRI -- Dynamic Routing Capsule Networks for Mild Cognitive Impairment Diagnosis -- Deep Multi-modal Latent Representation Learning for Automated Dementia Diagnosis -- Dynamic Spectral Convolution Networks with Assistant Task Training for Early MCI diagnosis -- Bridging Imaging, Genetics, and Diagnosis in a Coupled Low-Dimensional Framework -- Global and Local Interpretability for Cardiac MRI Classification -- Let's agree to disagree: learning highly debatable multirater labelling -- Coidentifciation of group-level hole structures in brain networks via Hodge Laplacian -- Confident Head Circumference Measurement from Ultrasound with Real-time Feedback for Sonographers -- Image Reconstruction and Synthesis -- Detection and Correction of Cardiac MRI Motion Artefacts during Reconstruction from k-space -- Exploiting motionfor deep learning reconstruction of extremely-undersampled dynamic MRI -- VS-Net: Variable spitting network for accelerated parallel MRI reconstruction -- A Novel Loss Function Incorporating Imaging Acquisition Physics for PET Attenuation Map Generation using Deep Learning -- A Prior Learning Network for Joint Image and Sensitivity Estimation in Parallel MR Imaging -- Consensus Neural Network for Medical Image Denoising with Only Noisy Training Samples -- Consistent Brain Ageing Synthesis -- Hybrid Generative Adversarial Networks for Deep MR to CT Synthesis using Unpaired Data -- Arterial Spin Labeling Images Synthesis via Locally-constrained WGAN-GP Ensemble -- SkrGAN: Sketching-rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis -- Wavelet-Based Semi-Supervised Adversarial Learning for Synthesizing Realistic 7T from 3T MRI -- DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis.
En línea:	https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
Link:	https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i

22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part IV [documento electrónico] / Shen, Dinggang, ; Liu, Tianming, ; Peters, Terry M., ; Staib, Lawrence H., ; Essert, Caroline, ; Zhou, Sean, ; Yap, Pew-Thian, ; Khan, Ali,  . -  1 ed.  . - [s.l.] : Springer, 2019 . - XXXVIII, 809 p.
ISBN : 978-3-030-32251-9
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.

Palabras clave:	Visión por computador  Sistemas de reconocimiento de patrones  Inteligencia artificial  Informática Médica  Reconocimiento de patrones automatizado  Informática de la Salud
Índice Dewey:	006.37 Visión artificial
Resumen:	El conjunto de seis volúmenes LNCS 11764, 11765, 11766, 11767, 11768 y 11769 constituye las actas arbitradas de la 22.ª Conferencia Internacional sobre Computación de Imágenes Médicas e Intervención Asistida por Computadora, MICCAI 2019, celebrada en Shenzhen, China, en octubre de 2019. Los 539 artículos completos revisados ​​presentados fueron cuidadosamente revisados ​​y seleccionados entre 1730 presentaciones en un proceso de revisión doble ciego. Los artículos están organizados en las siguientes secciones temáticas: Parte I: imágenes ópticas; endoscopia; microscopía. Parte II: segmentación de imágenes; registro de imagen; imágenes cardiovasculares; crecimiento, desarrollo, atrofia y progresión. Parte III: reconstrucción y síntesis de neuroimágenes; segmentación de neuroimagen; imágenes por resonancia magnética ponderada por difusión; neuroimagen funcional (fMRI); neuroimagen variada. Parte IV: forma; predicción; detección y localización; aprendizaje automático; diagnóstico asistido por ordenador; Reconstrucción y síntesis de imágenes. Parte V: intervenciones asistidas por ordenador; MIC se encuentra con CAI. Parte VI: tomografía computarizada; Imágenes de rayos X.
Nota de contenido:	Shape -- A CNN-Based Framework for Statistical Assessment of Spinal Shape and Curvature in Whole-Body MRI Images of Large Populations -- Exploiting Reliability-guided Aggregation for the Assessment of Curvilinear Structure Tortuosity -- A Surface-theoretic Approach for Statistical Shape Modeling -- Shape Instantiation from A Single 2D Image to 3D Point Cloud with One-stage Learning -- Placental Flattening via Volumetric Parameterization with Dirichlet Energy Regularization -- Fast Polynomial Approximation to Heat Diffusion in Manifolds -- Hierarchical Multi-Geodesic Model for Longitudinal Analysis of Temporal Trajectories of Anatomical Shape and Covariates -- Clustering of longitudinal shape data sets using mixture of separate or branching trajectories -- Group-wise Graph Matching of Cortical Gyral Hinges -- Multi-view Graph Matching of Cortical Landmarks -- Patient-specific Conditional Joint Models of Shape, Image Features and Clinical Indicators -- Surface-Based Spatial Pyramid Matching of Cortical Regions for Analysis of Cognitive Performance -- Prediction -- Diagnosis-guided multi-modal feature selection for prognosis prediction of lung squamous cell carcinoma -- Graph convolution based attention model for personalized disease prediction -- Predicting Early Stages of Neurodegenerative Diseases via Multi-task Low-rank Feature Learning -- Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments Over Progressions -- Deep Granular Feature-Label Distribution Learning for Neuroimaging-based Infant Age Prediction -- End-to-End Dementia Status Prediction from Brain MRI using Multi-Task Weakly-Supervised Attention Network -- Unified Modeling of Imputation, Forecasting, and Prediction for AD Progression -- LSTM Network for Prediction of Hemorrhagic Transformation in Acute Stroke -- Inter-modality Dependence Induced Data Recovery for MCI Conversion Prediction -- Preprocessing, Prediction and Significance: Framework and Application to Brain Imaging -- Early Prediction of Alzheimer's Disease progression using Variational Autoencoder -- Integrating Heterogeneous Brain Networks for Predicting Brain Disease Conditions -- Detection and Localization -- Uncertainty-informed detection of epileptogenic brain malformations using Bayesian neural networks -- Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network -- Intracranial aneurysms detection in 3D cerebrovascular mesh model with ensemble deep learning -- Automated Noninvasive Seizure Detection and Localization Using Switching Markov Models and Convolutional Neural Networks -- Multiple Landmarks Detection using Multi-Agent Reinforcement Learning -- Spatiotemporal Breast Mass Detection Network (MD-Net) in 4D DCE-MRI Images -- Automated Pulmonary Embolism Detection from CTPA Images using an End-to-End Convolutional Neural Network -- Pixel-wise anomaly ratings using Variational Auto-Encoders -- HR-CAM: Precise Localization of pathology using multi-level learning in CNNs -- Novel Iterative Attention Focusing Strategy for Joint Pathology Localization and Diagnosis of MCI Progression -- Automatic Vertebrae Recognition from Arbitrary Spine MRI images by a Hierarchical Self-calibration Detection Framework -- Machine Learning -- Image data validation for medical systems -- Captioning Ultrasound Images Automatically -- Feature Transformers: Privacy Preserving Life Learning Framework for Healthcare Applications -- As easy as 1, 2... 4? Uncertainty in counting tasks for medical imaging -- Generalizable Feature Learning in the Presence of Data Bias and Domain Class Imbalance with Application to Skin Lesion Classification -- Learning task-specific and shared representations in medical imaging -- Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis -- Efficient Ultrasound Image Analysis Models with Sonographer Gaze Assisted Distillation -- Fetal Pose Estimation in Volumetric MRI using 3D Convolution Neural Network -- Multi-Stage Prediction Networks for Data Harmonization -- Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik's Cube -- Bayesian Volumetric Autoregressive generative models for better semisupervised learning with scarce Medical imaging data -- Data Augmentation for Regression Neural Networks -- A Dirty Multi-task Learning Method for Multi-modal Brain Imaging Genetics -- Robust and Discriminative Brain Genome Association Analysis -- Symmetric Dual Adversarial Connectomic Domain Alignment for Predicting Isomorphic Brain Graph From a Baseline Graph -- Harmonization of Infant Cortical Thickness using Surface-to-Surface Cycle-Consistent Adversarial Networks -- Quantifying Confounding Bias in Neuroimaging Datasets with Causal Inference -- Computer-aided Diagnosis -- Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification -- Deep Angular Embedding and Feature Correlation Attention for Breast MRI Cancer Analysis -- Fully Deep Learning for Slit-lamp Photo based NuclearCataract Grading -- Overcoming Data Limitation in Medical Visual Question Answering -- Multi-Instance Multi-Scale CNN for Medical Image Classification -- Improving Uncertainty Estimation in Convolutional Neural Networks Using Inter-rater Agreement -- Improving Skin Condition Classification with a Visual Symptom Checker Trained using Reinforcement Learning -- DScGANS: Integrate Domain Knowledge in Training Dual-Path Semi-Supervised Conditional Generative Adversarial Networks and S3VM for Ultrasonography Thyroid Nodules Classification -- Similarity steered generative adversarial network and adaptive transfer learning for malignancy characterization of hepatocellualr carcinoma -- Unsupervised Clustering of Quantitative Imaging Subtypes using Autoencoder and Gaussian Mixture Model -- Adaptive Sparsity Regularization Based Collaborative Clustering for Cancer Prognosis -- Coronary Artery Plaque Characterization from CCTA Scans using Deep Learning and Radiomics -- Response Estimation through SpatiallyOriented Neural Network and Texture Ensemble (RESONATE) -- STructural Rectal Atlas Deformation (StRAD) features for characterizing intra- and peri-wall chemoradiation response on MRI -- Dynamic Routing Capsule Networks for Mild Cognitive Impairment Diagnosis -- Deep Multi-modal Latent Representation Learning for Automated Dementia Diagnosis -- Dynamic Spectral Convolution Networks with Assistant Task Training for Early MCI diagnosis -- Bridging Imaging, Genetics, and Diagnosis in a Coupled Low-Dimensional Framework -- Global and Local Interpretability for Cardiac MRI Classification -- Let's agree to disagree: learning highly debatable multirater labelling -- Coidentifciation of group-level hole structures in brain networks via Hodge Laplacian -- Confident Head Circumference Measurement from Ultrasound with Real-time Feedback for Sonographers -- Image Reconstruction and Synthesis -- Detection and Correction of Cardiac MRI Motion Artefacts during Reconstruction from k-space -- Exploiting motionfor deep learning reconstruction of extremely-undersampled dynamic MRI -- VS-Net: Variable spitting network for accelerated parallel MRI reconstruction -- A Novel Loss Function Incorporating Imaging Acquisition Physics for PET Attenuation Map Generation using Deep Learning -- A Prior Learning Network for Joint Image and Sensitivity Estimation in Parallel MR Imaging -- Consensus Neural Network for Medical Image Denoising with Only Noisy Training Samples -- Consistent Brain Ageing Synthesis -- Hybrid Generative Adversarial Networks for Deep MR to CT Synthesis using Unpaired Data -- Arterial Spin Labeling Images Synthesis via Locally-constrained WGAN-GP Ensemble -- SkrGAN: Sketching-rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis -- Wavelet-Based Semi-Supervised Adversarial Learning for Synthesizing Realistic 7T from 3T MRI -- DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis.
En línea:	https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
Link:	https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i