Machine Learning in Medical Imaging
Springer International Publishing (Verlag)
978-3-319-02266-6 (ISBN)
Unsupervised Deep Learning for Hippocampus Segmentation in 7.0 Tesla MR Images.- Integrating Multiple Network Properties for MCI Identification.- Learning-Boosted Label Fusion for Multi-atlas Auto-Segmentation.- Volumetric Segmentation of Key Fetal Brain Structures in 3D Ultrasound.- Sparse Classification with MRI Based Markers for Neuromuscular Disease Categorization.- Fully Automatic Detection of the Carotid Artery from Volumetric Ultrasound Images Using Anatomical Position-Dependent LBP Features.- A Transfer-Learning Approach to Image Segmentation Across Scanners by Maximizing Distribution Similarity.- A New Algorithm of Electronic Cleansing for Weak Faecal-Tagging CT Colonography.- A Unified Approach to Shape Model Fitting and Non-rigid Registration.- A Bayesian Algorithm for Image-Based Time-to-Event Prediction.- Patient-Specific Manifold Embedding of Multispectral Images Using Kernel Combinations.- fMRI Analysis with Sparse Weisfeiler-Lehman Graph Statistics.- Patch-Based Segmentation without Registration: Application to Knee MRI.- Flow-Based Correspondence Matching in Stereovision.- Thickness NETwork (ThickNet) Features for the Detection of Prodromal AD.- Metric Space Structures for Computational Anatomy.- Discriminative Group Sparse Representation for Mild Cognitive Impairment Classification.- Temporally Dynamic Resting-State Functional Connectivity Networks for Early MCI Identification.- An Improved Optimization Method for the Relevance Voxel Machine.- Disentanglement of Session and Plasticity Effects in Longitudinal fMRI Studies.- Identification of Alzheimer's Disease Using Incomplete Multimodal Dataset via Matrix Shrinkage and Completion.- On Feature Relevance in Image-Based Prediction Models: An Empirical Study.- Decision Forests with Spatio-Temporal Features for Graph-Based Tumor Segmentation in 4D Lung CT.- Improving Probabilistic Image Registration via Reinforcement Learning and Uncertainty Evaluation.- HEp-2 Cell Image Classification: AComparative Analysis.- A 2.5D Colon Wall Flattening Model for CT-Based Virtual Colonoscopy.- Augmenting Auto-context with Global Geometric Features for Spinal Cord Segmentation.- Large-Scale Manifold Learning Using an Adaptive Sparse Neighbor Selection Approach for Brain Tumor Progression Prediction.- Ensemble Universum SVM Learning for Multimodal Classification of Alzheimer's Disease.- Joint Sparse Coding Spatial Pyramid Matching for Classification of Color Blood Cell Image.- Multi-task Sparse Classifier for Diagnosis of MCI Conversion to AD with Longitudinal MR Images.- Sparse Multimodal Manifold-Regularized Transfer Learning for MCI Conversion Prediction.
Erscheint lt. Verlag | 21.8.2013 |
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Reihe/Serie | Image Processing, Computer Vision, Pattern Recognition, and Graphics | Lecture Notes in Computer Science |
Zusatzinfo | XII, 262 p. 94 illus. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 427 g |
Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
Informatik ► Grafik / Design ► Digitale Bildverarbeitung | |
Mathematik / Informatik ► Informatik ► Software Entwicklung | |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Schlagworte | 3D ultrasound • Alzheimer's disease • classification • functional magnetic resonance imaging • Image Segmentation |
ISBN-10 | 3-319-02266-0 / 3319022660 |
ISBN-13 | 978-3-319-02266-6 / 9783319022666 |
Zustand | Neuware |
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