Algorithm of ICA-based poisson-noise reduction and its application to CT imaging

Jian Li; Xianhua Han

doi:10.1117/12.741275

14 November 2007 Algorithm of ICA-based poisson-noise reduction and its application to CT imaging

Jian Li, Xianhua Han

Proceedings Volume 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 678908 (2007) https://doi.org/10.1117/12.741275
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

CT (computed tomography) imaging is a technology which uses X-ray beams (radiation) and computers to form detailed, cross-sectional images of an area of anatomy. However, the random scattered X-ray in CT imaging system will reduce radiographic contrast greatly in CT images. In this paper, a four-step method is proposed for decoding CT images: first, the EGSnrc Monte Carlo simulation system is used to simulate CT imaging and simulated data will be validated by real experimental data in the same experimental conditions; second, scattered X-ray image simulated by EGSnrc will be transformed into ICA-domain (independent component analysis-domain) to obtain the main magnitude of scattering data; third, a noise-reduction algorithm based on ICA-domain shrinkage is applied to smooth the CT image; fourth, the conventional linear deconvolution follows. The simulation results show that the reconstructed image is dramatically improved in comparison to that without the noise-removing filters, and the proposed method is also applied to real experimental X-ray imaging.

Citation Download Citation

Jian Li and Xianhua Han "Algorithm of ICA-based poisson-noise reduction and its application to CT imaging", Proc. SPIE 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 678908 (14 November 2007); https://doi.org/10.1117/12.741275

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