A Combined Regularization Method Using Prior Structural Information for Sound-Speed Image Reconstruction of Ultrasound Computed Tomography

Zisheng Yao,Xiaolei Qu,Shangchun Fan,Yoshikazu Nakajima

doi:10.1109/access.2020.3000062

Zisheng Yao, Xiaolei Qu + Show 2 more

Open Access

https://doi.org/10.1109/access.2020.3000062

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Abstract

Ultrasound computed tomography (USCT) is a promising technique for breast imaging. It provides three modalities: echo image, sound speed image (SSI), and attenuation image. The echo image reveals structural details of the breast with high resolution but is not quantitative. The SSI is quantitative, but its resolution is generally lower than that of the echo image. The SSI reconstruction is an ill-posed problem, thus the Tikhonov or total variation (TV) regularization methods are generally used. Tikhonov regularization is stable, but it tends to smooth the SSI and results in low resolution. TV regularization can preserve the sharp edges and provide higher resolution, but it may result in staircase artifacts. To combine the advantages of Tikhonov and TV regularizations, this article proposes a combined regularization method using prior structural information from the echo image. The proposed method mainly includes three steps. First, the echo image is reconstructed using the synthetic aperture (SA) technique and then segmented into breast and water regions. The segmentation result is used as prior structural information. Second, the USCT sound propagation forward model was built. Finally, with a penalty term according to the prior structural information, the combined regularization method is used to reconstruct the SSI. Both simulation and ex vivo experiments were conducted for evaluation. In the simulation, the proposed method has a low root-mean-square-error (13.78 m/s), a high correlation coefficient (0.812), a high structural similarity (0.755), and a low standard deviation of water sound speed (2.33 m/s). In the ex vivo experiment, the method has a low standard deviation of water sound speed (1.44 and 3.13 m/s for small and large objects, respectively), a low contrast to noise ratio (3.09 and 5.08), and a high Dice coefficient (0.92 and 0.97). Thus, the proposed combined regularization method using prior structural information can improve reconstruction quality.

Highlights

With the continuous increase in breast cancer incidence worldwide [1], breast cancer imaging is becoming increasingly important for both screening and diagnosis.The associate editor coordinating the review of this manuscript and approving it for publication was K
The echo image is segmented into breast and water regions, which is used as the prior structural information for reconstruction
Based on the characteristics of the widely used Tikhonov regularization and total variation (TV) regularization methods, we propose a combined regularization method using the prior structural information from echo image

Summary

Introduction

With the continuous increase in breast cancer incidence worldwide [1], breast cancer imaging is becoming increasingly important for both screening and diagnosis. The associate editor coordinating the review of this manuscript and approving it for publication was K. There are three general imaging modalities for breast cancer detection and diagnosis, namely X-ray mammography [2], B-mode ultrasound [3], [4], and magnetic resonance imaging (MRI) [5]. X-ray mammography has been widely used for breast cancer screening. Mammography exposes women to ionizing radiation, and only provides two-dimensional (2D) projection images of the breast.

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