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Patch-Based Techniques in Medical Imaging

Second International Workshop, Patch-MI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings

  • Conference proceedings
  • © 2016

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Editors:
  1. Guorong Wu

    1. University of North Carolina at Chapel Hill, Chapel Hill, USA

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  2. Pierrick Coupé

    1. Bordeaux University , Bordeaux, France

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  3. Yiqiang Zhan

    1. Siemens Healthcare , Malvern, USA

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  4. Brent C. Munsell

    1. College of Charleston , Charleston, USA

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  5. Daniel Rueckert

    1. Imperial College London , London, United Kingdom

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 9993)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: Patch-MI 2016.

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About this book

This book constitutes the refereed proceedings of the Second International Workshop on Patch-Based Techniques in Medical Images, Patch-MI 2016, which was held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016.

The 17 regular papers presented in this volume were carefully reviewed and selected from 25 submissions.

The main aim of the Patch-MI 2016 workshop is to promote methodological advances within the medical imaging field, with various applications in image segmentation, image denoising, image super-resolution, computer-aided diagnosis, image registration, abnormality detection, and image synthesis.

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Keywords

Table of contents (17 papers)

  1. Front Matter

    Pages I-X
    Download chapter PDF

  2. Automatic Segmentation of Hippocampus for Longitudinal Infant Brain MR Image Sequence by Spatial-Temporal Hypergraph Learning

    • Yanrong Guo, Pei Dong, Shijie Hao, Li Wang, Guorong Wu, Dinggang Shen
    Pages 1-8

  3. Construction of Neonatal Diffusion Atlases via Spatio-Angular Consistency

    • Behrouz Saghafi, Geng Chen, Feng Shi, Pew-Thian Yap, Dinggang Shen
    Pages 9-16

  4. Selective Labeling: Identifying Representative Sub-volumes for Interactive Segmentation

    • Imanol Luengo, Mark Basham, Andrew P. French
    Pages 17-24

  5. Robust and Accurate Appearance Models Based on Joint Dictionary Learning Data from the Osteoarthritis Initiative

    • Anirban Mukhopadhyay, Oscar Salvador Morillo Victoria, Stefan Zachow, Hans Lamecker
    Pages 25-33

  6. Consistent Multi-Atlas Hippocampus Segmentation for Longitudinal MR Brain Images with Temporal Sparse Representation

    • Lin Wang, Yanrong Guo, Xiaohuan Cao, Guorong Wu, Dinggang Shen
    Pages 34-42

  7. Sparse-Based Morphometry: Principle and Application to Alzheimer’s Disease

    • Pierrick CoupĂ©, Charles-Alban Deledalle, Charles Dossal, Michèle Allard, Alzheimer’s Disease Neuroimaging Initiative
    Pages 43-50

  8. Multi-Atlas Based Segmentation of Brainstem Nuclei from MR Images by Deep Hyper-Graph Learning

    • Pei Dong, Yangrong Guo, Yue Gao, Peipeng Liang, Yonghong Shi, Qian Wang et al.
    Pages 51-59

  9. Patch-Based Discrete Registration of Clinical Brain Images

    • Adrian V. Dalca, Andreea Bobu, Natalia S. Rost, Polina Golland
    Pages 60-67

  10. Non-local MRI Library-Based Super-Resolution: Application to Hippocampus Subfield Segmentation

    • Jose E. Romero, Pierrick CoupĂ©, Jose V. ManjĂłn
    Pages 68-75

  11. Patch-Based DTI Grading: Application to Alzheimer’s Disease Classification

    • Kilian Hett, Vinh-Thong Ta, RĂ©mi Giraud, Mary Mondino, JosĂ© V. ManjĂłn, Pierrick CoupĂ© et al.
    Pages 76-83

  12. Hierarchical Multi-Atlas Segmentation Using Label-Specific Embeddings, Target-Specific Templates and Patch Refinement

    • Christoph Arthofer, Paul S. Morgan, Alain Pitiot
    Pages 84-91

  13. HIST: HyperIntensity Segmentation Tool

    • Jose V. ManjĂłn, Pierrick CoupĂ©, Parnesh Raniga, Ying Xia, Jurgen Fripp, Olivier Salvado
    Pages 92-99

  14. Supervoxel-Based Hierarchical Markov Random Field Framework for Multi-atlas Segmentation

    • Ning Yu, Hongzhi Wang, Paul A. Yushkevich
    Pages 100-108

  15. CapAIBL: Automated Reporting of Cortical PET Quantification Without Need of MRI on Brain Surface Using a Patch-Based Method

    • Vincent Dore, Pierrick Bourgeat, Victor L. Villemagne, Jurgen Fripp, Lance Macaulay, Colin L. Masters et al.
    Pages 109-116

  16. High Resolution Hippocampus Subfield Segmentation Using Multispectral Multiatlas Patch-Based Label Fusion

    • JosĂ© E. Romero, Pierrick Coupe, JosĂ© V. ManjĂłn
    Pages 117-124

  17. Identification of Water and Fat Images in Dixon MRI Using Aggregated Patch-Based Convolutional Neural Networks

    • Liang Zhao, Yiqiang Zhan, Dominik Nickel, Matthias Fenchel, Berthold Kiefer, Xiang Sean Zhou
    Pages 125-132

  18. Estimating Lung Respiratory Motion Using Combined Global and Local Statistical Models

    • Zhong Xue, Ramiro Pino, Bin Teh
    Pages 133-140

  19. Back Matter

    Pages 141-141
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Other volumes

  1. Patch-Based Techniques in Medical Imaging

Editors and Affiliations

  • University of North Carolina at Chapel Hill, Chapel Hill, USA

    Guorong Wu

  • Bordeaux University , Bordeaux, France

    Pierrick Coupé

  • Siemens Healthcare , Malvern, USA

    Yiqiang Zhan

  • College of Charleston , Charleston, USA

    Brent C. Munsell

  • Imperial College London , London, United Kingdom

    Daniel Rueckert

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