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Multimodal Brain Image Analysis

Third International Workshop, MBIA 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013, Proceedings

  • Conference proceedings
  • © 2013

Overview

Editors:
  1. Li Shen

    1. Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, USA

  2. Tianming Liu

    1. Cortical Architecture Imaging and Discovery Lab, Department of Computer Science, University of Georgia, Athens, USA

  3. Pew-Thian Yap

    1. Department of Radiology and Biomedical Research Imaging Center (BRIC), The University of North Carolina at Chapel Hill, U.S.A.

  4. Heng Huang

    1. Computer Science and Engineering, University of Texas at Arlington, Arlington, USA

  5. Dinggang Shen

    1. Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA

  6. Carl-Fredrik Westin

    1. Surgical Planning Laboratory, BWH, Harvard Medical School, Boston, USA

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 8159)

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

Included in the following conference series:

Conference proceedings info: MBIA 2013.

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  • 9 Citations

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About this book

This book constitutes the refereed proceedings of the Third International Workshop on Multimodal Brain Image Analysis, MBIA 2013, held in Nagoya, Japan, on September 22, 2013 in conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI. The 24 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on analysis, methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience and clinical applications.

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Table of contents (24 papers)

  1. Front Matter

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  2. Locally Weighted Multi-atlas Construction

    • Junning Li, Yonggang Shi, Ivo D. Dinov, Arthur W. Toga
    Pages 1-8

  3. Assessing Structural Organization and Functional Interaction in Gyral, Sulcal and Cortical Networks

    • Xiaojin Li, Xintao Hu, Xi Jiang, Lei Guo, Junwei Han, Tianming Liu
    Pages 9-17

  4. Quantification and Analysis of Large Multimodal Clinical Image Studies: Application to Stroke

    • Ramesh Sridharan, Adrian V. Dalca, Kaitlin M. Fitzpatrick, Lisa Cloonan, Allison Kanakis, Ona Wu et al.
    Pages 18-30

  5. Modeling 4D Changes in Pathological Anatomy Using Domain Adaptation: Analysis of TBI Imaging Using a Tumor Database

    • Bo Wang, Marcel Prastawa, Avishek Saha, Suyash P. Awate, Andrei Irimia, Micah C. Chambers et al.
    Pages 31-39

  6. Bi-modal Non-rigid Registration of Brain MRI Data Based on Deconvolution of Joint Statistics

    • David Pilutti, Maddalena Strumia, Stathis Hadjidemetriou
    Pages 40-50

  7. Atlas Based Intensity Transformation of Brain MR Images

    • Snehashis Roy, Amod Jog, Aaron Carass, Jerry L. Prince
    Pages 51-62

  8. Use of Diffusion Tensor Images in Glioma Growth Modeling for Radiotherapy Target Delineation

    • Florian Dittmann, Björn Menze, Ender Konukoglu, Jan Unkelbach
    Pages 63-73

  9. Superpixel-Based Segmentation of Glioblastoma Multiforme from Multimodal MR Images

    • Po Su, Jianhua Yang, Hai Li, Linda Chi, Zhong Xue, Stephen T. Wong
    Pages 74-83

  10. Mapping Dynamic Changes in Ventricular Volume onto Baseline Cortical Surfaces in Normal Aging, MCI, and Alzheimer’s Disease

    • Sarah K. Madsen, Boris A. Gutman, Shantanu H. Joshi, Arthur W. Toga, Clifford R. Jack Jr., Michael W. Weiner et al.
    Pages 84-94

  11. Unsupervised Fiber Bundles Registration Using Weighted Measures Geometric Demons

    • Viviana Siless, Sergio Medina, Pierre Fillard, Bertrand Thirion
    Pages 95-106

  12. Classification Forests and Markov Random Field to Segment Chronic Ischemic Infarcts from Multimodal MRI

    • Jhimli Mitra, Pierrick Bourgeat, Jurgen Fripp, Soumya Ghose, Stephen Rose, Olivier Salvado et al.
    Pages 107-118

  13. Registration of Brain CT Images to an MRI Template for the Purpose of Lesion-Symptom Mapping

    • Hugo J. Kuijf, J. Matthijs Biesbroek, Max A. Viergever, Geert Jan Biessels, Koen L. Vincken
    Pages 119-128

  14. A Dynamical Clustering Model of Brain Connectivity Inspired by the N-Body Problem

    • Gautam Prasad, Josh Burkart, Shatanu H. Joshi, Talia M. Nir, Arthur W. Toga, Paul M. Thompson
    Pages 129-137

  15. Cortical Surface Analysis of Multi-contrast MR Data to Improve Detection of Cortical Pathology in Multiple Sclerosis

    • Marika Archambault-Wallenburg, Douglas Arnold, Sridar Narayanan, G. Bruce Pike, D. Louis Collins
    Pages 138-149

  16. PARP1 Gene Variation and Microglial Activity on [11C]PBR28 PET in Older Adults at Risk for Alzheimer’s Disease

    • Sungeun Kim, Kwangsik Nho, Shannon L. Risacher, Mark Inlow, Shanker Swaminathan, Karmen K. Yoder et al.
    Pages 150-158

  17. A Graph-Based Integration of Multimodal Brain Imaging Data for the Detection of Early Mild Cognitive Impairment (E-MCI)

    • Dokyoon Kim, Sungeun Kim, Shannon L. Risacher, Li Shen, Marylyn D. Ritchie, Michael W. Weiner et al.
    Pages 159-169

  18. Whole Brain Functional Connectivity Using Multi-scale Spatio-Spectral Random Effects Model

    • Hakmook Kang, Xue Yang, Frederick W. Bryan, Christina M. Tripp, Bennett A. Landman
    Pages 170-179

  19. Modeling Cognitive Processes via Multi-stage Consistent Functional Response Detection

    • Jinglei Lv, Dajiang Zhu, Xi Jiang, Kaiming Li, Xintao Hu, Junwei Han et al.
    Pages 180-188

  20. Bivariate Genome-Wide Association Study of Genetically Correlated Neuroimaging Phenotypes from DTI and MRI through a Seemingly Unrelated Regression Model

    • Neda Jahanshad, Priya Bhatt, Derrek P. Hibar, Julio E. Villalon, Talia M. Nir, Arthur W. Toga et al.
    Pages 189-201
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Other volumes

  1. Multimodal Brain Image Analysis

Editors and Affiliations

  • Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, USA

    Li Shen

  • Cortical Architecture Imaging and Discovery Lab, Department of Computer Science, University of Georgia, Athens, USA

    Tianming Liu

  • Department of Radiology and Biomedical Research Imaging Center (BRIC), The University of North Carolina at Chapel Hill, U.S.A.

    Pew-Thian Yap

  • Computer Science and Engineering, University of Texas at Arlington, Arlington, USA

    Heng Huang

  • Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA

    Dinggang Shen

  • Surgical Planning Laboratory, BWH, Harvard Medical School, Boston, USA

    Carl-Fredrik Westin

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