Information Processing in Medical Imaging
Springer Berlin (Verlag)
978-3-642-38867-5 (ISBN)
Matched Signal Detection on Graphs: Theory and Application to BrainNetwork Classification.- Exploring High-Order Functional Interactions via Structurally-Weighted LASSO Models.- Feature-Based Alignment of Volumetric Multi-modal Images.- Bayesian Estimation of Regularization and Atlas Building in Diffeomorphic Image Registration.- Gradient Competition Anisotropy for Centerline Extraction and Segmentation of Spinal Cords.- Automated Segmentation of the Cerebellar Lobules Using BoundarySpecific Classification and Evolution.- Tree-Space Statistics and Approximations for Large-Scale Analysis of Anatomical Trees.- Predicting Cognitive Data from Medical Images Using Sparse Linear Regression.- A Multiple Hypothesis Based Method for Particle Tracking and ItsExtension for Cell Segmentation.- A Multiple Model Probability Hypothesis Density Tracker for Time-Lapse Cell Microscopy Sequences.- Multi-layer Deformation Estimation for Fluoroscopic Imaging.- Fiber Connectivity Integrated Brain Activation Detection.- Diffeomorphic Metric Mapping of Hybrid Diffusion Imaging Based on BFOR Signal Basis.- Hyperbolic Harmonic Brain Surface Registration with Curvature-Based Landmark Matching.- Geometric Tree Kernels: Classification of COPD from Airway TreeGeometry.- Segmenting the Papillary Muscles and the Trabeculae from HighResolution Cardiac CT through Restoration of Topological Handles.- Data-Driven Interactive 3D Medical Image Segmentation Based onStructured Patch Model.- Sparse Deformable Models with Application to Cardiac Motion Analysis.- A Longitudinal Functional Analysis Framework for Analysis of White Matter Tract Statistics.- Groupwise Simultaneous Manifold Alignment for High-Resolution Dynamic MR Imaging of Respiratory Motion.- Conformal Mapping via Metric Optimization with Applicationfor Cortical Label Fusion.- A Novel Sparse Group Gaussian Graphical Model for Functional Connectivity Estimation.- Joint Co-Segmentation and Registration of 3D Ultrasound Images.- DeformableModeling Using a 3D Boundary Representation with Quadratic Constraints on the Branching Structure of the Blum Skeleton.- Sparse Projections of Medical Images onto Manifolds.- Efficient 3D Multi-region Prostate MRI Segmentation Using DualOptimization.- Locality Preserving Non-negative Basis Learning with GraphEmbedding.- Hierarchical Discriminative Framework for Detecting TubularStructures in 3D Images.- Joint Fractional Segmentation and Multi-tensor Estimation in Diffusion MRI.- Retrospective Estimation of the Susceptibility Driven Field Map for Distortion Correction in Echo Planar Imaging.- Group-Wise Cortical Correspondence via Sulcal Curve-Constrained Entropy Minimization.- Diffeomorphic Spectral Matching of Cortical Surfaces.- The Non-Local Bootstrap - Estimation of Uncertainty in Diffusion MRI.- Beyond Crossing Fibers: Tractography Exploiting Sub-voxel Fibre Dispersion and Neighbourhood Structure.- Learning from M/EEG Data with Variable Brain Activation Delays.- Unsupervised Learning of Functional Network Dynamics in Resting State fMRI.- Cohort-Level Brain Mapping: Learning Cognitive Atoms to Single Out Specialized Regions.- Torso Image AnalysisRapid Multi-organ Segmentation Using Context Integration andDiscriminative Models.- Edge- and Detail-Preserving Sparse Image Representations for Deformable Registration of Chest MRI and CT Volumes.- Multimodal Surface Matching: Fast and Generalisable CorticalRegistration Using Discrete Optimisation.- Globally Optimal Cortical Surface Matching with Exact Landmark Correspondence.- Joint Learning of Appearance and Transformation for Predicting Brain MR Image Registration.- Automatic Prostate MR Image Segmentation with Sparse Label Propagation and Domain-Specific Manifold Regularization.- Moving Frames for Heart Fiber Geometry.- Structural Brain Network Constrained Neuroimaging Marker Identification for Predicting Cognitive Functions.- Multi-atlas Segmentation with Robust Label Transfer and LabelFusion.- AHierarchical
| Erscheint lt. Verlag | 7.6.2013 |
|---|---|
| Reihe/Serie | Image Processing, Computer Vision, Pattern Recognition, and Graphics | Lecture Notes in Computer Science |
| Zusatzinfo | XXIV, 782 p. 312 illus. |
| Verlagsort | Berlin |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 1253 g |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Medizinische Fachgebiete ► Radiologie / Bildgebende Verfahren ► Radiologie | |
| Schlagworte | 3D images • Bildgebende Verfahren (Medizin) • Image Registration • Image Segmentation • Magnetic Resonance Imaging • ultrasound images |
| ISBN-10 | 3-642-38867-1 / 3642388671 |
| ISBN-13 | 978-3-642-38867-5 / 9783642388675 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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