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Machine Learning in Medical Imaging

Third International Workshop, MLMI 2012, Held in Conjunction with MICCAI 2012, Nice, France, October 1, 2012, Revised Selected Papers

  • Conference proceedings
  • © 2012

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Editors:
  1. Fei Wang

    1. IBM Research Almaden, San Jose, USA

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  2. Dinggang Shen

    1. School of Medicine, Department of Radiology and Biomedical Reserach Imaging Center, University of North Carolina, Chapel Hill, USA

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  3. Pingkun Yan

    1. Chinese Academy of Sciences, Xi’an Institute of Optics and Precision Mechanics, Shaanxi, China

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  4. Kenji Suzuki

    1. Department of Radiology, The University of Chicago, Chicago, USA

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  • High quality selected papers
  • Unique visibility
  • State of the art research

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 7588)

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

Included in the following conference series:

Conference proceedings info: MLMI 2012.

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Table of contents (33 papers)

  1. Front Matter

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  2. Transductive Prostate Segmentation for CT Image Guided Radiotherapy

    • Yinghuan Shi, Shu Liao, Yaozong Gao, Daoqiang Zhang, Yang Gao, Dinggang Shen
    Pages 1-9

  3. Model-Driven Centerline Extraction for Severely Occluded Major Coronary Arteries

    • Yefeng Zheng, Jianhua Shen, Huseyin Tek, Gareth Funka-Lea
    Pages 10-18

  4. MRI Confirmed Prostate Tissue Classification with Laplacian Eigenmaps of Ultrasound RF Spectra

    • Mehdi Moradi, Christian Wachinger, Andriy Fedorov, William M. Wells, Tina Kapur, Luciant D. Wolfsberger et al.
    Pages 19-26

  5. Hierarchical Ensemble of Multi-level Classifiers for Diagnosis of Alzheimer’s Disease

    • Manhua Liu, Daoqiang Zhang, Pew-Thian Yap, Dinggang Shen
    Pages 27-35

  6. Dense Deformation Reconstruction via Sparse Coding

    • Yonghong Shi, Guorong Wu, Zhijian Song, Dinggang Shen
    Pages 36-44

  7. Group Sparsity Constrained Automatic Brain Label Propagation

    • Shu Liao, Daoqiang Zhang, Pew-Thian Yap, Guorong Wu, Dinggang Shen
    Pages 45-53

  8. Sparse Patch-Guided Deformation Estimation for Improved Image Registration

    • Minjeong Kim, Guorong Wu, Dinggang Shen
    Pages 54-62

  9. Computer-Aided Detection of Aneurysms in 3D Time-of-Flight MRA Datasets

    • Santiago Suniaga, Rene Werner, Andre Kemmling, Michael Groth, Jens Fiehler, Nils Daniel Forkert
    Pages 63-69

  10. Data Driven Constraints for the SVM

    • Sune Darkner, Line H. Clemmensen
    Pages 70-77

  11. Towards Improving the Accuracy of Sensorless Freehand 3D Ultrasound by Learning

    • Juliette Conrath, Catherine Laporte
    Pages 78-85

  12. A Novel 3D Joint MGRF Framework for Precise Lung Segmentation

    • Behnoush Abdollahi, Ahmed Soliman, A. C. Civelek, X. -F. Li, G. Gimel’farb, Ayman El-Baz
    Pages 86-93

  13. Nonlinear Discriminant Graph Embeddings for Detecting White Matter Lesions in FLAIR MRI

    • Samuel Kadoury, Guray Erus, Christos Davatzikos
    Pages 94-102

  14. Use of Pattern-Information Analysis in Vision Science: A Pragmatic Examination

    • Mathieu J. Ruiz, Jean-Michel Hupé, Michel Dojat
    Pages 103-110

  15. Human Age Estimation with Surface-Based Features from MRI Images

    • Jieqiong Wang, Dai Dai, Meng Li, Jing Hua, Huiguang He
    Pages 111-118

  16. Biomedical Images Classification by Universal Nearest Neighbours Classifier Using Posterior Probability

    • Roberto D’Ambrosio, Wafa Bel Haj Ali, Richard Nock, Paolo Soda, Frank Nielsen, Michel Barlaud
    Pages 119-127

  17. Simultaneous Registration and Segmentation by L1 Minimization

    • Pratik Shah, Mithun Das Gupta
    Pages 128-135

  18. On the Creation of Generic fMRI Feature Networks Using 3-D Moment Invariants

    • Loizos Markides, Duncan Fyfe Gillies
    Pages 136-143

  19. Description and Classification of Confocal Endomicroscopic Images for the Automatic Diagnosis of Inflammatory Bowel Disease

    • Sara Couceiro, João P. Barreto, Paulo Freire, Pedro Figueiredo
    Pages 144-151

  20. A Localized MKL Method for Brain Classification with Known Intra-class Variability

    • Aydın Ulaş, Mehmet Gönen, Umberto Castellani, Vittorio Murino, Marcella Bellani, Michele Tansella et al.
    Pages 152-159
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  1. Machine Learning in Medical Imaging

Keywords

About this book

This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Medical Imaging, MLMI 2012, held in conjunction with MICCAI 2012, in Nice, France, in October 2012.
The 33 revised full papers presented were carefully reviewed and selected from 67 submissions. The main aim of this workshop is to help advance the scientific research within the broad field of machine learning in medical imaging. It focuses on major trends and challenges in this area, and it presents work aimed to identify new cutting-edge techniques and their use in medical imaging.

Editors and Affiliations

  • IBM Research Almaden, San Jose, USA

    Fei Wang

  • School of Medicine, Department of Radiology and Biomedical Reserach Imaging Center, University of North Carolina, Chapel Hill, USA

    Dinggang Shen

  • Chinese Academy of Sciences, Xi’an Institute of Optics and Precision Mechanics, Shaanxi, China

    Pingkun Yan

  • Department of Radiology, The University of Chicago, Chicago, USA

    Kenji Suzuki

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