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 /

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 wer...

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Bibliographic Details
Corporate Authors: Patch-MI (Workshop) Munich, Germany), SpringerLink (Online service), International Conference on Medical Image Computing and Computer-Assisted Intervention
Other Authors: Wu, Guorong (Researcher in medical imaging) (Editor), Coupé, Pierrick (Editor), Zhan, Yiqiang (Editor), Munsell, Brent (Editor), Rueckert, Daniel (Editor)
Format: Conference Proceeding eBook
Language:English
Published: Cham : Springer, 2015.
Series:Lecture notes in computer science ; 9467.
LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics.
Physical Description:
1 online resource (ix, 216 pages) : color illustrations.
Subjects:
Diagnostic imaging -- Data processing -- Congresses.
Online Access:SpringerLink - Click here for access
Contents:
  • A Multi-level Canonical Correlation Analysis Scheme for Standard-dose 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.

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