Automatic labeling of MR brain images through extensible learning and atlas forests.

Journal: Medical physics
Published Date: Oct 24, 2017

Abstract

PURPOSE: Multiatlas-based method is extensively used in MR brain images segmentation because of its simplicity and robustness. This method provides excellent accuracy although it is time consuming and limited in terms of obtaining information about new atlases. In this study, an automatic labeling of MR brain images through extensible learning and atlas forest is presented to address these limitations.

Authors

  • Lijun Xu
    School of Mathematics and Computer Science, Panzhihua University, Panzhihua, Sichuan 617000, China.
  • Hong Liu
    Key Laboratory of Grain and Oil Processing and Food Safety of Sichuan Province, College of Food and Bioengineering, Xihua University Chengdu 610039 China xingyage1@163.com.
  • Enmin Song
    School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
  • Meng Yan
    School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
  • Renchao Jin
    School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
  • Chih-Cheng Hung
    Center for Machine Vision and Security Research, Kennesaw State University, Marietta, GA, 30144, USA.

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