Recursive Bayesian estimation of respiratory motion using a modified autoregressive transition model

Ashrani Aizzuddin Abd. Rahni; Emma Lewis; Kevin Wells

doi:10.1117/12.2006878

13 March 2013 Recursive Bayesian estimation of respiratory motion using a modified autoregressive transition model

Ashrani Aizzuddin Abd. Rahni, Emma Lewis, Kevin Wells

Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 866935 (2013) https://doi.org/10.1117/12.2006878
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Compensation for respiratory motion has been identified as a crucial factor in achieving high resolution Nuclear Medicine (NM) imaging. Many motion correction approaches have been studied and they are seen to have advantages over simpler approaches such as respiratory gating. However, all motion correction approaches rely on an assumption or estimation of respiratory motion. This paper builds upon previous work in recursive Bayesian estimation of respiratory motion assuming a stereo camera observation of the motion of the external torso surface. This paper compares the performance of a modified autoregressive transition model against the previously presented linear transition model used when estimating motion within a 4D dataset generated from the XCAT phantom.

Citation Download Citation

Ashrani Aizzuddin Abd. Rahni, Emma Lewis, and Kevin Wells "Recursive Bayesian estimation of respiratory motion using a modified autoregressive transition model", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 866935 (13 March 2013); https://doi.org/10.1117/12.2006878

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