A denoising auto-encoder based on projection domain for low dose CT

Jiayu Duan, Ti Bai, Jianmei Cai, Xiaogang Chen, Xuanqin Mou

Research output: Chapter in Book/Report/Conference proceedingConference contribution


There are growing concerns on the effect of the radiation, which can be decreased by reducing X-ray tube current. However, this manner will lead to the degraded image due to the quantum noise. In order to alleviate the problem, multiple methods have been explored both during reconstruction and in post-processing. Recently, Denoising Auto-Encoder(DAE) has drawn much attention which can generate clean images from corrupted input. Inspired by the idea of DAE, during the low dose acquisition, the noisy projection can be regarded as corrupted images. In this paper, we proposed a denoising method based on projection domain. First, the DAE is train from stimulation noisy data coupled with original data. Then utilize the DAE to correct noisy projection and get denoised image from statistical iterative reconstruction. With the implement of DAE in projection domain, the reconstructions show clearer details in soft tissue and have higher SSIM (structural similarity index) than other denoising methods in image domain.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2018
Subtitle of host publicationPhysics of Medical Imaging
EditorsTaly Gilat Schmidt, Guang-Hong Chen, Joseph Y. Lo
ISBN (Electronic)9781510616356
StatePublished - 2018
Externally publishedYes
EventMedical Imaging 2018: Physics of Medical Imaging - Houston, United States
Duration: Feb 12 2018Feb 15 2018

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


OtherMedical Imaging 2018: Physics of Medical Imaging
Country/TerritoryUnited States


  • Computed Tomography
  • Denoising Auto-Encoder(DAE)
  • low dose
  • projection domain

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomaterials
  • Radiology Nuclear Medicine and imaging


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