Perceptual thresholds for differences in CT noise texture.

IF 1.9 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Journal of Medical Imaging Pub Date : 2024-05-01 Epub Date: 2024-05-09 DOI:10.1117/1.JMI.11.3.035501
Luuk J Oostveen, Kirsten Boedeker, Daniel Shin, Craig K Abbey, Ioannis Sechopoulos
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引用次数: 0

Abstract

Purpose: The average (fav) or peak (fpeak) noise power spectrum (NPS) frequency is often used as a one-parameter descriptor of the CT noise texture. Our study develops a more complete two-parameter model of the CT NPS and investigates the sensitivity of human observers to changes in it.

Approach: A model of CT NPS was created based on its fpeak and a half-Gaussian fit (σ) to the downslope. Two-alternative forced-choice staircase studies were used to determine perceptual thresholds for noise texture, defined as parameter differences with a predetermined level of discrimination performance (80% correct). Five imaging scientist observers performed the forced-choice studies for eight directions in the fpeak/σ-space, for two reference NPSs (corresponding to body and lung kernels). The experiment was repeated with 32 radiologists, each evaluating a single direction in the fpeak/σ-space. NPS differences were quantified by the noise texture contrast (Ctexture), the integral of the absolute NPS difference.

Results: The two-parameter NPS model was found to be a good representation of various clinical CT reconstructions. Perception thresholds for fpeak alone are 0.2  lp/cm for body and 0.4  lp/cm for lung NPSs. For σ, these values are 0.15 and 2  lp/cm, respectively. Thresholds change if the other parameter also changes. Different NPSs with the same fpeak or fav can be discriminated. Nonradiologist observers did not need more Ctexture than radiologists.

Conclusions: fpeak or fav is insufficient to describe noise texture completely. The discrimination of noise texture changes depending on its frequency content. Radiologists do not discriminate noise texture changes better than nonradiologists.

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CT 噪音纹理差异的感知阈值。
目的:平均(fav)或峰值(fpeak)噪声功率谱(NPS)频率通常被用作 CT 噪声纹理的单参数描述符。我们的研究建立了一个更完整的 CT 噪声功率谱双参数模型,并研究了人类观察者对其变化的敏感性:方法:根据 CT NPS 的峰值和下坡的半高斯拟合(σ)建立了一个 CT NPS 模型。使用双备选强迫选择阶梯研究来确定噪声纹理的感知阈值,该阈值被定义为具有预定辨别性能水平(80% 正确率)的参数差异。五名成像科学家观察员在 fpeak/σ 空间的八个方向上对两个参考 NPS(对应于体核和肺核)进行了强迫选择研究。该实验由 32 位放射科医生重复进行,每位医生评估 fpeak/σ 空间中的一个方向。NPS差异通过噪声纹理对比度(Ctexture)进行量化,Ctexture是NPS绝对差异的积分:结果:发现双参数 NPS 模型能很好地代表各种临床 CT 重建。仅对 fpeak 的感知阈值而言,体部 NPS 为 0.2 lp/cm,肺部 NPS 为 0.4 lp/cm。对于 σ,这些值分别为 0.15 和 2 lp/cm。如果其他参数也发生变化,阈值也会发生变化。具有相同峰值或阈值的不同 NPS 可以被区分开来。结论:fpeak 或 fav 不足以完全描述噪声纹理。对噪声纹理的辨别会随着其频率含量的变化而变化。放射科医生对噪声纹理变化的辨别能力并不比非放射科医生强。
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来源期刊
Journal of Medical Imaging
Journal of Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.10
自引率
4.20%
发文量
0
期刊介绍: JMI covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal. The scope of JMI includes: Imaging physics, Tomographic reconstruction algorithms (such as those in CT and MRI), Image processing and deep learning, Computer-aided diagnosis and quantitative image analysis, Visualization and modeling, Picture archiving and communications systems (PACS), Image perception and observer performance, Technology assessment, Ultrasonic imaging, Image-guided procedures, Digital pathology, Biomedical applications of biomedical imaging. JMI allows for the peer-reviewed communication and archiving of scientific developments, translational and clinical applications, reviews, and recommendations for the field.
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