Automatic labeling of MR brain images by hierarchical learning of atlas forests.

Journal: Medical physics
Published Date: Mar 1, 2016

Abstract

PURPOSE: Automatic brain image labeling is highly demanded in the field of medical image analysis. Multiatlas-based approaches are widely used due to their simplicity and robustness in applications. Also, random forest technique is recognized as an efficient method for labeling, although there are several existing limitations. In this paper, the authors intend to address those limitations by proposing a novel framework based on the hierarchical learning of atlas forests.

Authors

  • Lichi Zhang
    School of Biomedical Engineering, Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China.
  • Qian Wang
    Department of Radiation Oncology, China-Japan Union Hospital of Jilin University, Changchun, China.
  • Yaozong Gao
  • Guorong Wu
    Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Dinggang Shen
    School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.

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