Dataset Information

Noise reduction in dual-energy computed tomography virtual monoenergetic imaging.

ABSTRACT:

Purpose

Virtual monoenergetic images (VMIs) derived from dual-energy computed tomography (DECT) have been explored for several clinical applications in recent years. However, VMIs at low and high keVs have high levels of noise. The aim of this study was to reduce image noise in VMIs by using a two-step noise reduction technique.

Methods

VMI was first denoised using a modified highly constrained backprojection (HYPR) method. After the first-step denoising, a general-threshold filtering method was performed. Two sets of anthropomorphic phantoms were scanned with a clinical dual-source DECT system. DECT data (80/140Sn kV) were reconstructed as VMI series at 12 different energy levels (range, 40-150 keV, interval, 10 keV). For comparison, the averaged VMIs obtained from 10 repeated DECT scans were used as the reference standard. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and root-mean-square error (RMSE) were used to evaluate the quality of VMIs.

Results

Compared to the original HYPR method, the proposed two-step image denoising method could provide better performance in terms of SNR, CNR, and RMSE. In addition, the proposed method could achieve effective noise reduction while preserving edges and small structures, especially for low-keV VMIs.

Conclusion

The proposed two-step image denoising method is a feasible method for reducing noise in VMIs obtained from a clinical DECT scanner. The proposed method can also reduce edge blurring and the loss of intensity in small lesions.

SUBMITTER: Liu CK

PROVIDER: S-EPMC6753738 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Publications

Noise reduction in dual-energy computed tomography virtual monoenergetic imaging.

Liu Chi-Kuang CK Huang Hsuan-Ming HM

Journal of applied clinical medical physics 20190807 9

<h4>Purpose</h4>Virtual monoenergetic images (VMIs) derived from dual-energy computed tomography (DECT) have been explored for several clinical applications in recent years. However, VMIs at low and high keVs have high levels of noise. The aim of this study was to reduce image noise in VMIs by using a two-step noise reduction technique.<h4>Methods</h4>VMI was first denoised using a modified highly constrained backprojection (HYPR) method. After the first-step denoising, a general-threshold filte ...[more]

PMID: 31390137

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Project description:ObjectivesTo investigate whether the increased soft tissue contrast of virtual monoenergetic images (VMIs) obtained from a spectral detector computed tomography (SDCT) system improves washout assessment of arterially hyper-enhancing liver lesions.MethodsFifty-nine arterially hyper-enhancing lesions in 31 patients (age 65 ± 9 years, M/W 20/11) were included in this IRB-approved study. All patients underwent multi-phase SDCT for HCC screening. MRI, CEUS or biopsy within 3 months served as standard of reference to classify lesions as LiRADS 3 or 4/5. VMIs and conventional images (CIs) were reconstructed. Visual analysis was performed on 40, 60, and 80 kiloelectronvolt (keV) and CIs by 3 radiologists. Presence and visibility of washout were assessed; image quality and confidence of washout evaluation were evaluated on 5-point Likert scales. Signal-to-noise ratio (SNR), lesion-to-liver contrast-to-noise ratio (CNR) (|HUlesion-HUliver|/SDliver) and washout (|HUlesion-HUliver|) were calculated. Statistical assessment was performed using ANOVA and Wilcoxon test.ResultsOn subjective lesion analysis, the highest level of diagnostic confidence and highest sensitivity for the detection of lesion washout were found for 40-keV VMIs (40 keV vs. CI, 81.3 vs. 71.3%). Image quality parameters were significantly better in low-kiloelectronvolt VMIs than in CIs (p < 0.05; e.g. SNRliver: 40 keV vs. CIs, 12.5 ± 4.1 vs. 5.6 ± 1.6). In LiRADS 4/5 lesions, CNR and quantitative washout values were significantly higher in 40-keV VMIs compared to CIs (p < 0.05; e.g. CNR and washout in 40 keV vs. CIs, 2.3 ± 1.6 vs. 0.8 ± 0.5 and 29.0 ± 19.1 vs. 12.9 ± 6.9 HU, respectively).ConclusionBy increasing lesion contrast, low-kiloelectronvolt VMIs obtained from SDCT improve washout assessment of hyper-enhancing liver lesions with respect to washout visibility and diagnostic confidence.Key points• Low-kiloelectronvolt virtual monoenergetic images from spectral detector CT facilitate washout assessment in arterially hyper-enhancing liver lesions. • Image quality and quantitative washout parameters as well as subjective washout visibility and diagnostic confidence benefit from low-kiloelectronvolt virtual monoenergetic images.

Dataset Information

Noise reduction in dual-energy computed tomography virtual monoenergetic imaging.

Purpose

Methods

Results

Conclusion

Publications

Noise reduction in dual-energy computed tomography virtual monoenergetic imaging.

Similar Datasets

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