A practical reconstruction algorithm for CT noise variance maps using FBP reconstruction

Lei Zhu; Josh StarLack

doi:10.1117/12.713692

14 March 2007 A practical reconstruction algorithm for CT noise variance maps using FBP reconstruction

Lei Zhu, Josh StarLack

Proceedings Volume 6510, Medical Imaging 2007: Physics of Medical Imaging; 651023 (2007) https://doi.org/10.1117/12.713692
Event: Medical Imaging, 2007, San Diego, CA, United States

Abstract

Accurate prediction of reconstructed noise in computed tomography (CT) images is important for purposes of system design, optimization and evaluation. A large body of work describes noise prediction methods for CT, the vast majority of which assume stationarity of both noise and signal processes. Consequently, these methods are usually applied to and evaluated using simple phantoms, and only a portion of the image is scrutinized. In this work, we derive a practical method for reconstructing CT noise variance maps for arbitrary objects. Photon Poisson noise and system electronic noise are considered. The final formula has the same structure as that of the filtered backprojection (FBP) formula, but with different weighting factors and convolution kernels. The algorithm is verified using computer simulations of the Shepp-Logan phantom, and a good match is found between the predicted noise map from one single noisy scan and the measured noise using 128 noisy scans. As compared to other proposed noise models, our complementary work provides a method of noise prediction by simple adaptation of FBP reconstruction algorithms. The result is a tool that can be useful for system optimization and evaluation tasks as well as the design of reconstruction filters.

Citation Download Citation

Lei Zhu and Josh StarLack "A practical reconstruction algorithm for CT noise variance maps using FBP reconstruction", Proc. SPIE 6510, Medical Imaging 2007: Physics of Medical Imaging, 651023 (14 March 2007); https://doi.org/10.1117/12.713692

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