Quantitative Evaluation of Scatter Correction in 128‑slice Fan‑Beam Computed Tomography Scan using Geant4 Application for Tomographic Emission Monte Carlo Simulation

Article Type:
Research/Original Article (دارای رتبه معتبر)

Simulation of tomographic imaging systems with fan‑beam geometry, estimation of scattered beam profile using Monte Carlo techniques, and scatter correction using estimated data have always been new challenges in the field of medical imaging. The most important aspect is to ensure the results of the simulation and the accuracy of the scatter correction. This study aims to simulate 128‑slice computed tomography (CT) scan using the Geant4 Application for Tomographic Emission (GATE) program, to assess the validity of this simulation and estimate the scatter profile. Finally, a quantitative comparison of the results is made from scatter correction.


In this study, 128‑slice CT scan devices with fan‑beam geometry along with two phantoms were simulated by GATE program. Two validation methods were performed to validate the simulation results. The data obtained from scatter estimation of the simulation was used in a projection‑based scatter correction technique, and the post-correction results were analyzed using four quantities, such as: pixel intensity, CT number inaccuracy, contrast‑to‑noise ratio (CNR), and signal‑to‑noise ratio (SNR).


Both validation methods have confirmed the appropriate accuracy of the simulation. In the quantitative analysis of the results before and after the scatter correction, it should be said that the pixel intensity patterns were close to each other, and the accuracy of the CT scan number reached <10%. Moreover, CNR and SNR have increased by more than 30%–65% respectively in all studied areas.


The comparison of the results before and after scatter correction shows an improvement in CNR and SNR while a reduction in cupping artifact according to pixel intensity pattern and enhanced CT number accuracy

Journal of Medical Signals and Sensors, Volume:13 Issue: 4, Oct-Dec 2023
280 to 289
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 1,390,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!