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

Chi‐Kuang Liu,Hsuan‐Ming Huang

doi:10.1002/acm2.12694

Abstract

PurposeVirtual 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.MethodsVMI 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.ResultsCompared 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.ConclusionThe 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.

Highlights

After introduction of the first commercial dual‐source dual‐energy computed tomography (DECT) system in 2006,1 several DECT‐based techniques including iodine map, virtual non‐contrast and effective atomic number have been proposed.[2,3] These DECT‐based techniques offer a wide variety of clinical applications.[2,3] In particular, virtual monoenergetic images (VMIs) derived from DECT images have shown encouraging results and gained popularity recently.[4]
In order to further improve the image quality of DECT‐based VMIs, we proposed a two‐step noise reduction technique using a combination of HYPR17,18 and the general‐threshold filtering (GTF) method.[22]
It is clear that the loss of intensity in edges and small lesions can be greatly reduced using the proposed method compared to highly constrained backprojection (HYPR)

Summary

Introduction

After introduction of the first commercial dual‐source dual‐energy computed tomography (DECT) system in 2006,1 several DECT‐based techniques including iodine map, virtual non‐contrast and effective atomic number have been proposed.[2,3] These DECT‐based techniques offer a wide variety of clinical applications.[2,3] In particular, virtual monoenergetic images (VMIs) derived from DECT images have shown encouraging results and gained popularity recently.[4] Clinical applications of DECT‐based VMIs include metal artifact reduction, beam‐hardening correction,[5,6] contrast and noise optimization,[7,8] and material differentiation.[9,10] In addition, DECT‐based VMIs can be used to assess fatty liver[11] and hypervascularized abdominal tumors.[12] Despite promising results obtained in recent investigations, the noise levels of DECT‐based VMIs were high at low and high keVs.[7,8,13,14]

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Methods

Results

Conclusion