Low-dose CT reconstruction assisted by a global CT image manifold prior

Chenyang Shen; Guoyang Ma; Xun Jia

doi:10.1117/12.2534959

28 May 2019 Low-dose CT reconstruction assisted by a global CT image manifold prior

Chenyang Shen, Guoyang Ma, Xun Jia

Proceedings Volume 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine; 1107205 (2019) https://doi.org/10.1117/12.2534959
Event: Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, Philadelphia, United States

Abstract

The use of X-ray Computed Tomography (CT) leads to the concern of lifetime cancer risk. Low-dose CT scan with reduced mAs can reduce the radiation exposure, but the image quality is usually degraded due to excessive image noise. Numerous studies have been conducted to regularize CT image during reconstruction for better image quality. In this paper, we propose a fully data-driven manifold learning approach. An auto-encoder-decoder convolutional neural network is established to map an entire CT image to the inherent low-dimensional manifold, and then to restore the CT image from its manifold representation. A novel reconstruction algorithm assisted by the leant manifold prior is developed to achieve high quality low-dose CT reconstruction. We perform comprehensive simulation studies using patient abdomen CT images. The trained network is capable of restoring high-quality CT images with average error of ~ 20 HU. The manifold prior assisted reconstruction scheme achieves high-quality low-dose CT reconstruction, with average reconstruction error of ~ 38.5 HU, 4.6 times and 3 times lower than that of filtered back projection method and total-variation based iterative reconstruction method, respectively.

Citation Download Citation

Chenyang Shen, Guoyang Ma, and Xun Jia "Low-dose CT reconstruction assisted by a global CT image manifold prior", Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 1107205 (28 May 2019); https://doi.org/10.1117/12.2534959

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available