Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
Springer International Publishing (Verlag)
978-3-030-32250-2 (ISBN)
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.
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 Predi
| Erscheinungsdatum | 20.10.2019 |
|---|---|
| Reihe/Serie | Image Processing, Computer Vision, Pattern Recognition, and Graphics | Lecture Notes in Computer Science |
| Zusatzinfo | XXXVIII, 809 p. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 1276 g |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Technik | |
| Schlagworte | Applications • Artificial Intelligence • Computed tomography • Computer Aided Diagnosis • computer assisted interventions • Computer Science • conference proceedings • Image Processing • image reconstruction • Image Segmentation • Imaging Systems • Informatics • Learning Algorithms • machine learning • Medical Images • Neural networks • neuroimage reconstruction • neuroimage segmentation • Optical imaging • Research • segmentation methods • Support Vector Machines • SVM • x-ray imaging |
| ISBN-10 | 3-030-32250-5 / 3030322505 |
| ISBN-13 | 978-3-030-32250-2 / 9783030322502 |
| Zustand | Neuware |
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