An improved combination of ordered subsets and momentum for fast model-based iterative CT reconstruction

V. Haase; K. Stierstorfer; K. Hahn; H. Schöndube; A. Maier; F. Noo

doi:10.1117/12.2549733

16 March 2020 An improved combination of ordered subsets and momentum for fast model-based iterative CT reconstruction

V. Haase, K. Stierstorfer, K. Hahn, H. Schöndube, A. Maier, F. Noo

Proceedings Volume 11312, Medical Imaging 2020: Physics of Medical Imaging; 113121N (2020) https://doi.org/10.1117/12.2549733
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States

Abstract

Model-based iterative CT reconstruction suffers from its high computational cost. To increase the reconstruction speed, algorithms using a momentum acceleration can be combined with the ordered subset approach. As shown in previous works, the incorporation of ordered subsets strongly improves the reconstruction time but makes the outcome of the reconstruction difficult to predict due to its empirical nature. Specifically, when the number of subsets is too high, divergence or convergence to an unsatisfactory result can easily appear. In this work, we propose a new combination of ordered subsets with momentum to achieve fast reconstruction in a more robust manner. Our approach, referred to as EOS-MFISTA, is an Efficient Ordered Subset strategy based on the steps of MFISTA, a monotonic version of FISTA. In short, EOS-MFISTA uses objective function values to decide on the next update step and does this with little increase in computational effort. The performance of EOS-MFISTA is evaluated on real CT data of a head phantom and a human chest. Starting from a zero image, 200 iterations of EOS-MFISTA are calculated and compared with other algorithms. Quantitative analyses based on the RMSE show that EOS-MFISTA is much more robust than OS-FISTA, especially when the number of subsets is increased to accelerate reconstruction. Visual inspection of results obtained with 50 iterations further supports these findings.

Conference Presentation

Citation Download Citation

V. Haase, K. Stierstorfer, K. Hahn, H. Schöndube, A. Maier, and F. Noo "An improved combination of ordered subsets and momentum for fast model-based iterative CT reconstruction", Proc. SPIE 11312, Medical Imaging 2020: Physics of Medical Imaging, 113121N (16 March 2020); https://doi.org/10.1117/12.2549733

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