arrow
返回

Scatter kernel estimation with an edge-spread function method for cone-beam computed tomography imaging

delete2008-11-07
delete98
PRE
AI
H
Heng Li *
R
Radhe Mohan
X
X Zhu
DOI:10.1088/0031-9155/53/23/006delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
The clinical applications of kilovoltage x-ray cone- beam computed tomography (CBCT) have been compromised by the limited quality of CBCT images, which typically is due to a substantial scatter component in the projection data. In this paper, we describe an experimental method of deriving the scatter kernel of a CBCT imaging system. The estimated scatter kernel can be used to remove the scatter component from the CBCT projection images, thus improving the quality of the reconstructed image. The scattered radiation was approximated as depth-dependent, pencil-beam kernels, which were derived using an edge-spread function (ESF) method. The ESF geometry was achieved with a half-beam block created by a 3 mm thick lead sheet placed on a stack of slab solid-water phantoms. Measurements for ten water-equivalent thicknesses (WET) ranging from 0 cm to 41 cm were taken with (half-blocked) and without (unblocked) the lead sheet, and corresponding pencil-beam scatter kernels or point-spread functions (PSFs) were then derived without assuming any empirical trial function. The derived scatter kernels were verified with phantom studies. Scatter correction was then incorporated into the reconstruction process to improve image quality. For a 32 cm diameter cylinder phantom, the flatness of the reconstructed image was improved from 22% to 5%. When the method was applied to CBCT images for patients undergoing image-guided therapy of the pelvis and lung, the variation in selected regions of interest (ROIs) was reduced from > 300 HU to < 100 HU. We conclude that the scatter reduction technique utilizing the scatter kernel effectively suppresses the artifact caused by scatter in CBCT.
Keyword:
X-RAY SCATTER
DIGITAL RADIOGRAPHY
GLARE CORRECTION
AIR GAPS
CT
CONVOLUTION
ALGORITHM
IMAGES
MODEL
COMPENSATION
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Physics in Medicine and Biology 封面图
Physics in Medicine and Biology
IF:
3.4
论文数:
1.4W
被引数:
3.1W

机构

U
university of texas system
学者数:
18.5W
论文数: 15.6W
被引数: 210
引用论文

引用论文

Positive Psychological Capital as a Predictor of Satisfaction With the Fly-In Fly-Out Model
err2021-07-19
err0
errOAAI
errNazaré Soares Marques; Miguel Pereira Lopes; Sónia P. Gonçalves
err分享
err收藏
Hit ratios
err1976-01-01
err0
errOAAI
errS. J. Waters
err分享
err收藏
Optimum design methodologies for pile foundations in London
err2014-12-01
err0
errOAAI
errChristos Letsios; Nikos D. Lagaros; Manolis Papadrakakis
err分享
err收藏
Characterization of scattered radiation in kV CBCT images using Monte Carlo simulations
err2006-10-24
err180
PREAI
errJarry, Genevieve; Graham, Sean A.; Moseley, Douglas J.; Jaffray, David J.; Siewerdsen, Jeffrey H.; Verhaegen, Frank
err分享
err收藏
err分享
err收藏
Segmental vibration transmissibility of seated occupant from lumped parameter models
err2011-10-26
err0
PREAI
errMasilamany Santha Alphin; Krishnaswamy Sankaranarayanasamy; Suthangathan Paramashivan Sivapirakasam
err分享
err收藏
err分享
err收藏
学者 查看更多内容