Patch-Based Techniques in Medical Imaging

A Multi-level Canonical Correlation Analysis Scheme for Standard-dosePET Image Estimation.- Image Super-Resolution by Supervised Adaption ofPatchwise Self-Similarity from High-Resolution Image.- Automatic HippocampusLabeling Using the Hierarchy of Sub-Region Random Forests.- Isointense InfantBrain Segmentation by Stacked Kernel Canonical Correlation Analysis.- ImprovingAccuracy of Automatic Hippocampus Segmentation in Routine MRI by FeaturesLearned from Ultra-high Field MRI.- Dual-Layer l1-Graph Embedding forSemi-Supervised Image Labeling.- Automatic Liver Tumor Segmentation inFollow-up CT Studies Using Convolutional Neural Network.- Block-basedStatistics for Robust Non-Parametric Morphometry.- Automatic CollimationDetection in Digital Radiographs with the Directed Hough Transform andLearning-based Edge Detection.- Efficient Lung Cancer Cell Detection with DeepConvolutional Neural Network.- An Effective Approach for Robust Lung CancerCell Detection.- Laplacian Shape Editing with Local Patch Based Force Field forInteractive Segmentation.- Hippocampus Segmentation through Distance FieldFusion.- Learning a Spatiotemporal Dictionary for Magnetic ResonanceFingerprinting with Compress Sensing.- Fast Regions-of-Interest Detection inWhole Slide Histopathology Images.- Reliability Guided Forward and BackwardPatch-based Method for Multi-atlas Segmentation.- Correlating Tumour Histologyand ex vivo MRI Using Dense Modality-Independent Patch-Based Descriptor.- Multi-AtlasSegmentation using Patch-Based Joint Label Fusion with Non-Negative LeastSquares Regression.- A Spatially Constrained Deep Learning Framework forDetection of Epithelial Tumor Nuclei in Cancer Histology Images.- 3D MRIDenoising using Rough Set Theory and Kernel Embedding Method.- A Novel CellOrientation Congruence Descriptor for Superpixel based Epithelium Segmentationin Endometrial Histology Images.- Patch-based Segmentation from MP2RAGE Images:Comparison to Conventional Techniques.-Multi-Atlas and Multi-Modal