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Proceedings Paper

Calibration free beam hardening correction for cardiac CT perfusion imaging
Author(s): Jacob Levi; Rachid Fahmi; Brendan L. Eck; Anas Fares; Hao Wu; Mani Vembar; Amar Dhanantwari; Hiram G. Bezerra; David L. Wilson
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Paper Abstract

Myocardial perfusion imaging using CT (MPI-CT) and coronary CTA have the potential to make CT an ideal noninvasive gate-keeper for invasive coronary angiography. However, beam hardening artifacts (BHA) prevent accurate blood flow calculation in MPI-CT. BH Correction (BHC) methods require either energy-sensitive CT, not widely available, or typically a calibration-based method. We developed a calibration-free, automatic BHC (ABHC) method suitable for MPI-CT. The algorithm works with any BHC method and iteratively determines model parameters using proposed BHA-specific cost function. In this work, we use the polynomial BHC extended to three materials. The image is segmented into soft tissue, bone, and iodine images, based on mean HU and temporal enhancement. Forward projections of bone and iodine images are obtained, and in each iteration polynomial correction is applied. Corrections are then back projected and combined to obtain the current iteration’s BHC image. This process is iterated until cost is minimized. We evaluate the algorithm on simulated and physical phantom images and on preclinical MPI-CT data. The scans were obtained on a prototype spectral detector CT (SDCT) scanner (Philips Healthcare). Mono-energetic reconstructed images were used as the reference. In the simulated phantom, BH streak artifacts were reduced from 12±2HU to 1±1HU and cupping was reduced by 81%. Similarly, in physical phantom, BH streak artifacts were reduced from 48±6HU to 1±5HU and cupping was reduced by 86%. In preclinical MPI-CT images, BHA was reduced from 28±6 HU to less than 4±4HU at peak enhancement. Results suggest that the algorithm can be used to reduce BHA in conventional CT and improve MPI-CT accuracy.

Paper Details

Date Published: 21 March 2016
PDF: 10 pages
Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 97843S (21 March 2016); doi: 10.1117/12.2216623
Show Author Affiliations
Jacob Levi, Case Western Reserve Univ. (United States)
Rachid Fahmi, Case Western Reserve Univ. (United States)
Brendan L. Eck, Case Western Reserve Univ. (United States)
Anas Fares, Univ. Hospitals Case Medical Ctr. (United States)
Hao Wu, Case Western Reserve Univ. (United States)
Mani Vembar, Philips Healthcare (United States)
Amar Dhanantwari, Philips Healthcare (United States)
Hiram G. Bezerra, Univ. Hospitals Case Medical Ctr. (United States)
David L. Wilson, Case Western Reserve Univ. (United States)

Published in SPIE Proceedings Vol. 9784:
Medical Imaging 2016: Image Processing
Martin A. Styner; Elsa D. Angelini, Editor(s)

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