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Proceedings Paper

Cone-beam Computed Tomography (CBCT) and CT image registration aided by CBCT-based synthetic CT
Author(s): Yabo Fu; Yang Lei; Yingzi Liu; Tonghe Wang; Walter J. Curran; Tian Liu; Pretesh Patel; Xiaofeng Yang
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Paper Abstract

CBCT has been widely integrated into modern linear accelerators in radiation therapy for image guidance purpose due to its cost effectiveness and low dose to patients. Planning CT images are registered with CBCT images for patient setup, contour propagations and dose calculations. However, it is challenging to accurately register the two since CBCT images often contain much image artifacts and noise, and intensity between CT and CBCT is not consistent. Therefore, traditional DIRs with intensity-based image similarity measures such as sum of squared differences, mean absolute differences are not applicable to CT-CBCT image registration. To address this issue, we propose to synthesize a high quality CT from CBCT to reduce image artifacts and perform intensity correction prior to image registration. Traditional Demons registration method was used to register the CT images with the CBCT-based synthetic CT (sCT). CT-sCT registration was tested on 5 patients’ datasets. On average, the mean absolute error between the fixed and deformed images were reduced from 102.2 to 92.4 HU by replacing CBCT with sCT.

Paper Details

Date Published: 10 March 2020
PDF: 7 pages
Proc. SPIE 11313, Medical Imaging 2020: Image Processing, 113132U (10 March 2020); doi: 10.1117/12.2549095
Show Author Affiliations
Yabo Fu, Emory Univ. (United States)
Yang Lei, Emory Univ. (United States)
Yingzi Liu, Emory Univ. (United States)
Tonghe Wang, Emory Univ. (United States)
Walter J. Curran, Emory Univ. (United States)
Tian Liu, Emory Univ. (United States)
Pretesh Patel, Emory Univ. (United States)
Xiaofeng Yang, Emory Univ. (United States)


Published in SPIE Proceedings Vol. 11313:
Medical Imaging 2020: Image Processing
Ivana Išgum; Bennett A. Landman, Editor(s)

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