Patch-Based Techniques in Medical Imaging
First International Workshop, Patch-MI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 9, 2015, Revised Selected Papers
Samenvatting
This book constitutes the thoroughly refereed
post-workshop proceedings of the First International Workshop on Patch-based Techniques
in Medical Images, Patch-MI 2015, which was held in conjunction with MICCAI
2015, in Munich, Germany, in October 2015.
The 25 full papers presented in this volume were
carefully reviewed and selected from 35 submissions. The topics covered are such
as image segmentation of anatomical structures or lesions; image enhancement;
computer-aided prognostic and diagnostic; multi-modality fusion; mono and multi
modal image synthesis; image retrieval; dynamic, functional physiologic and
anatomic imaging; super-pixel/voxel in medical image analysis; sparse
dictionary learning and sparse coding; analysis of 2D, 2D+t, 3D, 3D+t, 4D, and
4D+t data.
Specificaties
Inhoudsopgave
PET Image Estimation.- Image Super-Resolution by Supervised Adaption of
Patchwise Self-Similarity from High-Resolution Image.- Automatic Hippocampus
Labeling Using the Hierarchy of Sub-Region Random Forests.- Isointense Infant
Brain Segmentation by Stacked Kernel Canonical Correlation Analysis.- Improving
Accuracy of Automatic Hippocampus Segmentation in Routine MRI by Features
Learned from Ultra-high Field MRI.- Dual-Layer l1-Graph Embedding for
Semi-Supervised Image Labeling.- Automatic Liver Tumor Segmentation in
Follow-up CT Studies Using Convolutional Neural Network.- Block-based
Statistics for Robust Non-Parametric Morphometry.- Automatic Collimation
Detection in Digital Radiographs with the Directed Hough Transform and
Learning-based Edge Detection.- Efficient Lung Cancer Cell Detection with Deep
Convolutional Neural Network.- An Effective Approach for Robust Lung Cancer
Cell Detection.- Laplacian Shape Editing with Local Patch Based Force Field for
Interactive Segmentation.- Hippocampus Segmentation through Distance Field
Fusion.- Learning a Spatiotemporal Dictionary for Magnetic Resonance
Fingerprinting with Compress Sensing.- Fast Regions-of-Interest Detection in
Whole Slide Histopathology Images.- Reliability Guided Forward and Backward
Patch-based Method for Multi-atlas Segmentation.- Correlating Tumour Histology
and ex vivo MRI Using Dense Modality-Independent Patch-Based Descriptor.- Multi-Atlas
Segmentation using Patch-Based Joint Label Fusion with Non-Negative Least
Squares Regression.- A Spatially Constrained Deep Learning Framework for
Detection of Epithelial Tumor Nuclei in Cancer Histology Images.- 3D MRI
Denoising using Rough Set Theory and Kernel Embedding Method.- A Novel Cell
Orientation Congruence Descriptor for Superpixel based Epithelium Segmentation
in Endometrial Histology Images.- Patch-based Segmentation from MP2RAGE Images:
Comparison to Conventional Techniques.- Multi-Atlas and Multi-Modal Hippocampus
Segmentation for Infant MR Brain Images by Propagating Anatomical Labels on
Hypergraph.- Prediction of Infant MRI Appearance and Anatomical Structure
Evolution using Sparse Patch-based Metamorphosis Learning Framework.- Efficient
Multi-Scale Patch-based Segmentation.</p>