Choirul Anam - Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof Soedarto, SH Tembalang, Semarang ۵۰۲۷۵, Central Java, Indonesia
Riska Amilia - Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof Soedarto, SH Tembalang, Semarang ۵۰۲۷۵, Central Java, Indonesia
Ariij Naufal - Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof Soedarto, SH Tembalang, Semarang ۵۰۲۷۵, Central Java, Indonesia
Heri Sutanto - Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof Soedarto, SH Tembalang, Semarang ۵۰۲۷۵, Central Java, Indonesia
Yanurita Dwihapsari - Department of Physics, Faculty of Science and Data Analytics, Institute Teknologi Sepuluh Nopember, Kampus ITS Sukolilo – Surabaya ۶۰۱۱۱, East Java, Indonesia
Toshioh Fujibuchi - Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, ۳-۱-۱ Maidashi, Higashi-ku, Fukuoka ۸۱۲-۸۵۸۲, Japan
Geoff Dougherty - Department of Applied Physics and Medical Imaging, California State University Channel Islands, Camarillo, CA ۹۳۰۱۲, USA

Background: Methods for segmentation, i.e., Full-segmentation (FS) and Segmentation-rotation (SR), are proposed for maintaining Computed Tomography (CT) number linearity. However, their effectiveness has not yet been tested against noise.Objective: This study aimed to evaluate the influence of noise on the accuracy of CT number linearity of the FS and SR methods on American College of Radiology (ACR) CT and computational phantoms.Material and Methods: This experimental study utilized two phantoms, ACR CT and computational phantoms. An ACR CT phantom was scanned by a ۱۲۸-slice CT scanner with various tube currents from ۸۰ to ۲۰۰ mA to acquire various noises, with other constant parameters. The computational phantom was added by different Gaussian noises between ۲۰ and ۱۲۰ Hounsfield Units (HU). The CT number linearity was measured by the FS and SR methods, and the accuracy of CT number linearity was computed on two phantoms.Results: The two methods successfully segmented both phantoms at low noise, i.e., less than ۶۰ HU. However, segmentation and measurement of CT number linearity are not accurate on a computational phantom using the FS method for more than ۶۰-HU noise. The SR method is still accurate up to ۱۲۰ HU of noise. Conclusion: The SR method outperformed the FS method to measure the CT number linearity due to its endurance in extreme noise.

ACR CT Phantom, Computational Phantom, Diagnostic Imaging, Image Quality Enhancement, Noise, CT Number Linearity, Computed Tomography Scanner, Quality of Health Care