School of Computer Science, Hubei University of Technology, No. 28, Nanli Road, Hongshan District, Wuhan, China.
School of Life Science and Technology, Huazhong University of Science and Technology, No. 1037, Luoyu Road, Hongshan District, Wuhan, China.
Math Biosci Eng. 2022 Jul 19;19(10):10160-10175. doi: 10.3934/mbe.2022476.
Ultrasound computed tomography (USCT) has been developed for breast tumor screening. The sound-speed modal of USCT can provide quantitative sound-speed values to help tumor diagnosis. Time-of-flight (TOF) is the critical input in sound-speed reconstruction. However, we found that the missing data problem in the detected TOF causes artifacts on the reconstructed sound-speed images, which may affect the tumor identification. In this study, to address the missing TOF data problem, we first adopted the singular value threshold (SVT) algorithm to complete the TOF matrix. The threshold value in SVT is difficult to determine, so we proposed a selection strategy, that is, to enumerate the threshold values as the multiples of the maximum singular value of the incomplete matrix and then evaluate the image quality to select the proper threshold value. In the numerical breast phantom experiment, the artifacts are eliminated, and the accuracy is higher than the accuracy of the compared methods. In the in vivo experiment, we reconstructed the sound-speed image of the breast of a volunteer with invasive breast cancer, and the SVT algorithm improved the image sharpness. The completion of DTOF based on SVT gives better accuracy than the compared methods, but too large a threshold value decreases the accuracy. In the future, the selection method of the threshold value needs further research, and more USCT cases should be included in the experiments.
超声计算机断层扫描（USCT）已被开发用于乳腺肿瘤筛查。USCT 的声速模态可以提供定量声速值，以帮助肿瘤诊断。飞行时间（TOF）是声速重建的关键输入。然而，我们发现检测到的 TOF 中的缺失数据问题导致重建声速图像上出现伪影，这可能会影响肿瘤识别。在这项研究中，为了解决缺失的 TOF 数据问题，我们首先采用奇异值阈值（SVT）算法来完成 TOF 矩阵。SVT 中的阈值很难确定，因此我们提出了一种选择策略，即将阈值值枚举为不完整矩阵的最大奇异值的倍数，然后评估图像质量以选择适当的阈值值。在数值乳腺体模实验中，消除了伪影，并且准确性高于比较方法的准确性。在体内实验中，我们重建了一名患有浸润性乳腺癌的志愿者的乳腺声速图像，SVT 算法提高了图像的清晰度。基于 SVT 的 DTOF 完成的准确性优于比较方法，但过大的阈值会降低准确性。在未来，需要进一步研究阈值选择方法，并在实验中纳入更多 USCT 病例。
