Principle Analysis for the Possibility of Scattered X-Ray to Improve Computed Tomography Reconstruction

If scattered X-rays carry information that is independent of that is carried by primary X-rays, the accuracy of attenuation coefficients estimated using both primary and scattered X-rays is expected to be better than that estimated using only primary X-rays. However, because scattered X-rays cannot be easily introduced into conventional X-ray computed tomography (CT), the issue has gained scant attention. This study demonstrates theoretically that the measurement of scattered X-rays improves the accuracy of reconstruction in CT, even in a photoelectric absorption scenario. Here, the CT geometry was simplified for a system that targeted a homogeneous thin cylinder, retaining the necessary configuration. Furthermore, we constructed a mathematical model termed the π-junction model. This model is an extension of the T-junction model used in one of our previous studies. It addresses the photoelectric effect, which was not considered in the T-junction model. The variance in the estimation of the attenuation coefficients of this model from the measurements of both primary and scattered photons was evaluated as the Cramer-Rao lower bound. Both the theory and numerical experiments using Monte Carlo simulation showed that the accuracy of estimating the attenuation coefficient could be improved by measuring the scattered X-rays together with the primary X-rays, even in the presence of photoelectric absorption. This result provides a basis for the superiority of using scattered X-rays.

Authors

Institutions

Publication Details

Journal
IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences
Published
2025-01-29
DOI
https://doi.org/10.1587/transfun.2024eap1066
Primary Topic
Medical Imaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Principle Analysis for the Possibility of Scattered X-Ray to Improve Computed Tomography Reconstruction

Tetsuya Nakagami, Naohiro Toda
IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences
Medical Imaging Techniques and Applications
article

Principle Analysis for the Possibility of Scattered X-Ray to Improve Computed Tomography Reconstruction

Tetsuya Nakagami, Naohiro Toda
article en

Abstract

If scattered X-rays carry information that is independent of that is carried by primary X-rays, the accuracy of attenuation coefficients estimated using both primary and scattered X-rays is expected to be better than that estimated using only primary X-rays. However, because scattered X-rays cannot be easily introduced into conventional X-ray computed tomography (CT), the issue has gained scant attention. This study demonstrates theoretically that the measurement of scattered X-rays improves the accuracy of reconstruction in CT, even in a photoelectric absorption scenario. Here, the CT geometry was simplified for a system that targeted a homogeneous thin cylinder, retaining the necessary configuration. Furthermore, we constructed a mathematical model termed the π-junction model. This model is an extension of the T-junction model used in one of our previous studies. It addresses the photoelectric effect, which was not considered in the T-junction model. The variance in the estimation of the attenuation coefficients of this model from the measurements of both primary and scattered photons was evaluated as the Cramer-Rao lower bound. Both the theory and numerical experiments using Monte Carlo simulation showed that the accuracy of estimating the attenuation coefficient could be improved by measuring the scattered X-rays together with the primary X-rays, even in the presence of photoelectric absorption. This result provides a basis for the superiority of using scattered X-rays.

IEICE Transactions on Fundamentals of Electronics Communications and Computer SciencesVol. E108.A(8)
Aichi Prefectural University (JP), Denso (United States) (US)
Openalex Percentile: Top 98%
Medical Imaging Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.