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Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011

14th International Conference, Toronto, Canada, September 18-22, 2011, Proceedings, Part III

  • Conference proceedings
  • © 2011

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Editors:
  1. Gabor Fichtinger

    1. Queen’s University, Kingston, Canada

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  2. Anne Martel

    1. Sunnybrook Hospital, Toronto, Canada

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    You can also search for this editor in PubMed   Google Scholar

  3. Terry Peters

    1. Robarts Research Institute, London, Canada

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 6893)

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

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Conference proceedings info: MICCAI 2011.

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About this book

The three-volume set LNCS 6891, 6892 and 6893 constitutes the refereed proceedings of the 14th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011, held in Toronto, Canada, in September 2011. Based on rigorous peer reviews, the program committee carefully selected 251 revised papers from 819 submissions for presentation in three volumes. The third volume includes 82 papers organized in topical sections on computer-aided diagnosis and machine learning, and segmentation.

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Table of contents (82 papers)

  1. Front Matter

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  2. Computer Aided Diagnosis and Machine Learning I

    1. Sliding Window and Regression Based Cup Detection in Digital Fundus Images for Glaucoma Diagnosis

      • Yanwu Xu, Dong Xu, Stephen Lin, Jiang Liu, Jun Cheng, Carol Y. Cheung et al.
      Pages 1-8

    2. Learning from Only Positive and Unlabeled Data to Detect Lesions in Vascular CT Images

      • Maria A. Zuluaga, Don Hush, Edgar J. F. Delgado Leyton, Marcela Hernández Hoyos, Maciej Orkisz
      Pages 9-16

    3. Regularized Tensor Factorization for Multi-Modality Medical Image Classification

      • Nematollah Batmanghelich, Aoyan Dong, Ben Taskar, Christos Davatzikos
      Pages 17-24

    4. Detection, Grading and Classification of Coronary Stenoses in Computed Tomography Angiography

      • B. Michael Kelm, Sushil Mittal, Yefeng Zheng, Alexey Tsymbal, Dominik Bernhardt, Fernando Vega-Higuera et al.
      Pages 25-32

    5. Aggregated Distance Metric Learning (ADM) for Image Classification in Presence of Limited Training Data

      • Gaoyu Xiao, Anant Madabhushi
      Pages 33-40

    6. Sparse Classification for Computer Aided Diagnosis Using Learned Dictionaries

      • Meizhu Liu, Le Lu, Xiaojing Ye, Shipeng Yu, Marcos Salganicoff
      Pages 41-48

    7. A Discriminative-Generative Model for Detecting Intravenous Contrast in CT Images

      • Antonio Criminisi, Krishna Juluru, Sayan Pathak
      Pages 49-57

    8. Classification of Alzheimer’s Disease Using a Self-Smoothing Operator

      • Juan Eugenio Iglesias, Jiayan Jiang, Cheng-Yi Liu, Zhuowen Tu, the Alzheimers Disease Neuroimaging Initiative
      Pages 58-65

    9. An Analysis of Scale and Rotation Invariance in the Bag-of-Features Method for Histopathological Image Classification

      • S. Hussain Raza, R. Mitchell Parry, Richard A. Moffitt, Andrew N. Young, May D. Wang
      Pages 66-74

    10. Robust Large Scale Prone-Supine Polyp Matching Using Local Features: A Metric Learning Approach

      • Meizhu Liu, Le Lu, Jinbo Bi, Vikas Raykar, Matthias Wolf, Marcos Salganicoff
      Pages 75-82

    11. Targeted Optical Biopsies for Surveillance Endoscopies

      • Selen Atasoy, Diana Mateus, Alexander Meining, Guang-Zhong Yang, Nassir Navab
      Pages 83-90

    12. Focal Biologically Inspired Feature for Glaucoma Type Classification

      • Jun Cheng, Dacheng Tao, Jiang Liu, Damon Wing Kee Wong, Beng Hai Lee, Mani Baskaran et al.
      Pages 91-98

    13. The Relevance Voxel Machine (RVoxM): A Bayesian Method for Image-Based Prediction

      • Mert R. Sabuncu, Koen Van Leemput
      Pages 99-106

    14. Assessment of Regional Myocardial Function via Statistical Features in MR Images

      • Mariam Afshin, Ismail Ben Ayed, Kumaradevan Punithakumar, Max W. K. Law, Ali Islam, Aashish Goela et al.
      Pages 107-114

  3. Computer Aided Diagnosis and Machine Learning II

    1. Identifying AD-Sensitive and Cognition-Relevant Imaging Biomarkers via Joint Classification and Regression

      • Hua Wang, Feiping Nie, Heng Huang, Shannon Risacher, Andrew J. Saykin, Li Shen et al.
      Pages 115-123

    2. Biological Indexes Based Reflectional Asymmetry for Classifying Cutaneous Lesions

      • Zhao Liu, Lyndon Smith, Jiuai Sun, Melvyn Smith, Robert Warr
      Pages 124-132

    3. Identification of Paediatric Tuberculosis from Airway Shape Features

      • Benjamin Irving, Pierre Goussard, Robert Gie, Andrew Todd-Pokropek, Paul Taylor
      Pages 133-140

    4. Automatic Region-of-Interest Segmentation and Pathology Detection in Magnetically Guided Capsule Endoscopy

      • Philip W. Mewes, Dominik Neumann, Oleg Licegevic, Johannes Simon, Aleksandar Lj. Juloski, Elli Angelopoulou
      Pages 141-148

    5. Simultaneous Segmentation and Grading of Hippocampus for Patient Classification with Alzheimer’s Disease

      • Pierrick Coupé, Simon F. Eskildsen, José V. Manjón, Vladimir Fonov, D. Louis Collins
      Pages 149-157
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Other volumes

  1. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011

  2. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011

  3. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011

Editors and Affiliations

  • Queen’s University, Kingston, Canada

    Gabor Fichtinger

  • Sunnybrook Hospital, Toronto, Canada

    Anne Martel

  • Robarts Research Institute, London, Canada

    Terry Peters

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