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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

  • Conference proceedings
  • © 2015

Overview

Editors:
  1. Guorong Wu

    1. Univers 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 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 9467)

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 2015.

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About this book

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.

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Table of contents (25 papers)

  1. Front Matter

    Pages I-IX
    Download chapter PDF

  2. A Multi-level Canonical Correlation Analysis Scheme for Standard-Dose PET Image Estimation

    • Le An, Pei Zhang, Ehsan Adeli-Mosabbeb, Yan Wang, Guangkai Ma, Feng Shi et al.
    Pages 1-9

  3. Image Super-Resolution by Supervised Adaption of Patchwise Self-similarity from High-Resolution Image

    • Guorong Wu, Xiaofeng Zhu, Qian Wang, Dinggang Shen
    Pages 10-18

  4. Automatic Hippocampus Labeling Using the Hierarchy of Sub-region Random Forests

    • Lichi Zhang, Qian Wang, Yaozong Gao, Guorong Wu, Dinggang Shen
    Pages 19-27

  5. Isointense Infant Brain Segmentation by Stacked Kernel Canonical Correlation Analysis

    • Li Wang, Feng Shi, Yaozong Gao, Gang Li, Weili Lin, Dinggang Shen
    Pages 28-36

  6. Improving Accuracy of Automatic Hippocampus Segmentation in Routine MRI by Features Learned from Ultra-High Field MRI

    • Shuyu Li, Feng Shi, Guangkai Ma, Minjeong Kim, Dinggang Shen
    Pages 37-45

  7. Dual-Layer \(\ell _1\)-Graph Embedding for Semi-supervised Image Labeling

    • Qian Wang, Guorong Wu, Dinggang Shen
    Pages 46-53

  8. Automatic Liver Tumor Segmentation in Follow-Up CT Scans: Preliminary Method and Results

    • Refael Vivanti, Ariel Ephrat, Leo Joskowicz, Naama Lev-Cohain, Onur A. Karaaslan, Jacob Sosna
    Pages 54-61

  9. Block-Based Statistics for Robust Non-parametric Morphometry

    • Geng Chen, Pei Zhang, Ke Li, Chong-Yaw Wee, Yafeng Wu, Dinggang Shen et al.
    Pages 62-70

  10. Automatic Collimation Detection in Digital Radiographs with the Directed Hough Transform and Learning-Based Edge Detection

    • Liang Zhao, Zhigang Peng, Klaus Finkler, Anna Jerebko, Jason J. Corso, Xiang (Sean) Zhou
    Pages 71-78

  11. Efficient Lung Cancer Cell Detection with Deep Convolution Neural Network

    • Zheng Xu, Junzhou Huang
    Pages 79-86

  12. An Effective Approach for Robust Lung Cancer Cell Detection

    • Hao Pan, Zheng Xu, Junzhou Huang
    Pages 87-94

  13. Laplacian Shape Editing with Local Patch Based Force Field for Interactive Segmentation

    • Chaowei Tan, Zhennan Yan, Kang Li, Dimitris Metaxas, Shaoting Zhang
    Pages 95-103

  14. Hippocampus Segmentation Through Distance Field Fusion

    • Shumao Pang, Zhentai Lu, Wei Yang, Yao Wu, Zixiao Lu, Liming Zhong et al.
    Pages 104-111

  15. Learning a Spatiotemporal Dictionary for Magnetic Resonance Fingerprinting with Compressed Sensing

    • Pedro A. Gómez, Cagdas Ulas, Jonathan I. Sperl, Tim Sprenger, Miguel Molina-Romero, Marion I. Menzel et al.
    Pages 112-119

  16. Fast Regions-of-Interest Detection in Whole Slide Histopathology Images

    • Ruoyu Li, Junzhou Huang
    Pages 120-127

  17. Reliability Guided Forward and Backward Patch-Based Method for Multi-atlas Segmentation

    • Liang Sun, Chen Zu, Daoqiang Zhang
    Pages 128-136

  18. Correlating Tumour Histology and ex vivo MRI Using Dense Modality-Independent Patch-Based Descriptors

    • Andre Hallack, Bartłomiej W. Papież, James Wilson, Lai Mun Wang, Tim Maughan, Mark J. Gooding et al.
    Pages 137-145

  19. Multi-atlas Segmentation Using Patch-Based Joint Label Fusion with Non-Negative Least Squares Regression

    • Mattias P. Heinrich, Matthias Wilms, Heinz Handels
    Pages 146-153

  20. A Spatially Constrained Deep Learning Framework for Detection of Epithelial Tumor Nuclei in Cancer Histology Images

    • Korsuk Sirinukunwattana, Shan E. Ahmed Raza, Yee-Wah Tsang, David Snead, Ian Cree, Nasir Rajpoot
    Pages 154-162
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Other volumes

  1. Patch-Based Techniques in Medical Imaging

Editors and Affiliations

  • Univers 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 Munsell

  • Imperial College London, London, United Kingdom

    Daniel Rueckert

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