SDResU-Net: Separable and Dilated Residual U-Net for MRI Brain Tumor Segmentation.

Journal: Current medical imaging
Published Date: Jan 1, 2020

Abstract

BACKGROUND: Glioma is one of the most common and aggressive primary brain tumors that endanger human health. Tumors segmentation is a key step in assisting the diagnosis and treatment of cancer disease. However, it is a relatively challenging task to precisely segment tumors considering characteristics of brain tumors and the device noise. Recently, with the breakthrough development of deep learning, brain tumor segmentation methods based on fully convolutional neural network (FCN) have illuminated brilliant performance and attracted more and more attention.

Authors

  • Jianxin Zhang
    Key Lab of Advanced Design and Intelligent Computing (Ministry of Education), Dalian University, Dalian, China.
  • Xiaogang Lv
    Key Lab of Advanced Design and Intelligent Computing (Ministry of Education), Dalian University, Dalian, China.
  • Qiule Sun
    School of Information and Communication Engineering, Dalian University of Technology, Dalian, China.
  • Qiang Zhang
    Yunan Provincial Center for Disease Control and Prevention, Kunming 650022, China.
  • Xiaopeng Wei
    Key Lab of Advanced Design and Intelligent Computing (Ministry of Education), Dalian University, Dalian, China.
  • Bin Liu
    Department of Endocrinology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China; Department of Endocrinology, Neijiang First People's Hospital, Chongqing, China.

Keywords

External Resources

Popular Topics
Recent Journals