Two stage residual CNN for texture denoising and structure enhancement on low dose CT image.

Journal: Computer methods and programs in biomedicine
Published Date: Oct 8, 2019

Abstract

BACKGROUND AND OBJECTIVE: X-ray computed tomography (CT) plays an important role in modern medical science. Human health problems caused by CT radiation have attracted the attention of the academic community widely. Reducing radiation dose results in a deterioration in image quality and further affects doctor's diagnosis. Therefore, this paper introduces a new denoise method for low dose CT (LDCT) images, called two stage residual convolutional neural network (TS-RCNN).

Authors

  • Liangliang Huang
    Software College, Northeastern University, Shenyang 110819, China.
  • Huiyan Jiang
    Software College, Northeastern University, Shenyang 110819, China.
  • Shaojie Li
    Department of Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang 110819, China.
  • Zhiqi Bai
    Software College, Northeastern University, Shenyang 110819, China.
  • Jitong Zhang
    Sino-Dutch Biomedical and Information Engineering College, Northeastern University, Shenyang 110819, China.

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