Spatial resolution measurement for iterative reconstruction by use of image-averaging techniques in computed tomography

Urikura, Atsushi; Ichikawa, Katsuhiro; Hara, Takanori; Nishimaru, Eiji; Nakaya, Yoshihiro

doi:10.1007/s12194-014-0273-2

Cited by 44 publications

(23 citation statements)

References 26 publications

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“…This yielded a sufficiently high contrast-to-noise ratio (CNR) of the averaged image (≥25), according to a report in which the image averaging technique was used to improve the evaluation accuracy of the IR resolution property of a bar pattern phantom [9]. Our preliminary experiments involving this high CNR condition indicated that the standard deviation for five measurements fell within 0.007 for frequency ranges <10% MTFTask.…”

Section: Phantom Image Data Analysismentioning

confidence: 73%

Object shape dependency of in-plane resolution for iterative reconstruction of computed tomography

et al. 2017

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The present study aimed to investigate whether the in-plane resolution property of iterative reconstruction (IR) of computed tomography (CT) data is object shape-dependent by testing columnar shapes with diameters of 3, 7, and 10 cm (circular edge method) and a cubic shape with 5-cm side lengths (linear edge method). For each shape, objects were constructed of acrylic (contrast in Hounsfield units [∆HU] = 120) as well as a soft tissue equivalent material (∆HU = 50). For each shape, we measured the modulation transfer functions (MTFs) of IR and filtered back projection (FBP) using two multi-slice CT scanners at scan doses of 5 and 10 mGy. In addition, we evaluated a thin metal wire using the conventional method at 10 mGy. For FBP images, the MTF results of the tested objects and the wire method showed substantial agreement, thus demonstrating the validity of our analysis technique. For IR images, the MTF results of different shapes were nearly identical for each object contrast and dose combination, and we did not observe shape-dependent effects of the resolution properties of either tested IR. We conclude that both the circular edge method and linear edge method are equally useful for evaluating the resolution properties of IRs.

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Section: Phantom Image Data Analysismentioning

confidence: 73%

Object shape dependency of in-plane resolution for iterative reconstruction of computed tomography

et al. 2017

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“…For quantitative evaluations, non‐helical scanning with an 80 × 0.5 mm 2 detector configuration was performed to eliminate the influence of table movement on the image‐averaging process, as described later 17. For qualitative evaluation, helical scanning (pitch factor, 0.844) with a 32 × 1.0 mm 2 detector configuration was used, assuming clinical settings.…”

Section: Methodsmentioning

confidence: 99%

“…The acrylic phantom was placed at the isocenter of the CT scanner. To acquire low‐noise images for the MTF task analysis, 100 or more scans were performed with the same table position for each radiation dose level and these were averaged for each protocol using image‐averaging techniques 17. Furthermore, images were reacquired after the liquid in the phantom was adjusted with diluted contrast medium (60 HU) to obtain a contrast of 10 HU between background and soft tissue (70 HU).…”

Section: Methodsmentioning

confidence: 99%

“…Several previous studies have indicated that AIDR 3D improves image quality and reduces dose in a manner comparable to IR 15, 16. In contrast, it has also been reported that resolution changes in accordance with radiation dose, iterative strength, and contrast, and that low contrast detectability is not necessarily improved at low dose levels 17, 18…”

Section: Introductionmentioning

confidence: 98%

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Quantitative and qualitative evaluation of hybrid iterative reconstruction, with and without noise power spectrum models: A phantom study

Minamishima

Sugisawa

Yamada

et al. 2018

J Applied Clin Med Phys

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The purpose of this phantom study was to investigate the feasibility of dose reduction with hybrid iterative reconstruction, with and without a noise power spectrum (NPS) model, using both quantitative and qualitative evaluations. Standard dose (SD), three‐quarter dose (TQD), and half‐dose (HD) of radiation were used. Images were reconstructed with filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR 3D) (MILD, STR), and AIDR 3D enhanced (eAIDR 3D) (eMILD, eSTR). An NPS analysis, task‐based modulation transfer function (MTF task) analysis, and comparisons of low‐contrast detectability and image texture were performed. Although the eAIDR 3D had a higher NPS value in the high‐frequency range and improved image texture and resolution as compared with AIDR 3D at the same radiation dose and iteration levels, it yielded higher noise than AIDR 3D. Additionally, although there was no statistically significant difference between SD‐FBP and the TQD series in the comparison of the mean area under the curve (AUC), the mean AUC was statistically significantly different between SD‐FBP and the HD series. NPS values in the high‐frequency range, 10% MTF task values, low‐contrast detectability, and image textures of TQD‐eMILD were comparable to those of SD‐FBP. Our findings suggested that using eMILD can reduce the radiation dose by 25%, while potentially maintaining diagnostic performance, spatial resolution, and image texture; this could support selecting the appropriate protocol in a clinical setting.

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“…This technique has been widely used for MTF measurements of IR images. Most of the studies using this technique computed the average of the consecutive cross‐sectional images of the cylinder and/or the average of many images acquired from repeated scans to improve the signal‐to‐noise ratio …”

Section: Introductionmentioning

confidence: 99%

A pitfall of using the circular‐edge technique with image averaging for spatial resolution measurement in iteratively reconstructed CT images

Narita

Ohkubo

2020

J Applied Clin Med Phys

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The circular‐edge technique using a low‐contrast cylindrical object is commonly used to measure the modulation transfer functions (MTFs) in computed tomography (CT) images reconstructed with iterative reconstruction (IR) algorithms. This method generally entails averaging multiple images of the cylinder to reduce the image noise. We suspected that the cylinder edge shape depicted in the IR images might exhibit slight deformation with respect to the true shape because of the intrinsic nonlinearity of IR algorithms. Image averaging can reduce the image noise, but does not effectively improve the deformation of the edge shape; thereby causing errors in the MTF measurements. We address this issue and propose a method to correct the MTF. We scanned a phantom including cylindrical objects with a CT scanner (Ingenuity Elite, Philips Healthcare). We obtained cylinder images with iterative model reconstruction (IMR) algorithms. The images suggested that the depicted edge shape deforms and fluctuates depending on slice positions. Because of this deformation, image averaging can potentially cause additional blurring. We define the deformation function D that describes the additional blurring, and obtain D by analyzing multiple images. The MTF measured by the circular‐edge method (referred to as MTF') can be thought of as the multiplication of the true MTF by the Fourier transformation (FT) of D. We thus obtain the corrected MTF (MTFcorrected) by dividing MTF' by the FT of D. We validate our correction method by comparing the calculated images based on the convolution theorem using MTF' and MTFcorrected with the actual images obtained with the scanner. The calculated image using MTFcorrected is more similar to the actual image compared with the image calculated using MTF', particularly in edge regions. We describe a pitfall in MTF measurement using the circular‐edge technique with image averaging, and suggest a method to correct it.

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Spatial resolution measurement for iterative reconstruction by use of image-averaging techniques in computed tomography

Cited by 44 publications

References 26 publications

Object shape dependency of in-plane resolution for iterative reconstruction of computed tomography

Object shape dependency of in-plane resolution for iterative reconstruction of computed tomography

Quantitative and qualitative evaluation of hybrid iterative reconstruction, with and without noise power spectrum models: A phantom study

A pitfall of using the circular‐edge technique with image averaging for spatial resolution measurement in iteratively reconstructed CT images

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