Liu Bin, Xu Zhao, Wang Qifeng, Niu Xiaolei, Chan Wei Xuan, Hadi Wiputra, Yap Choon Hwai
International School of Information Science & Engineering (DUT-RUISE), Dalian University of Technology, Dalian, China.
Key Lab of Ubiquitous Network and Service Software of Liaoning Province, Dalian University of Technology, Dalian, China.
Quant Imaging Med Surg. 2021 Apr;11(4):1567-1585. doi: 10.21037/qims-20-818.
4D ultrasound images of human fetal heart are important for medical applications such as evaluation of fetal heart function and early diagnosis of congenital heart diseases. However, due to the high noise and low contrast characteristics in fetal ultrasound images, denoising and enhancements are important.
In this paper, a special method framework for denoising and enhancing is proposed. It consists of a 4D-NLM (non-local means) denoising method for 4D fetal heart ultrasound image sequence, which takes advantage of context similar information in neighboring images to denoise the target image, and an enhancing method called the Adaptive Clipping for Each Histogram Pillar (ACEHP), which is designed to enhance myocardial spaces to distinguish them from blood spaces.
Denoising and enhancing experiments show that 4D-NLM method has better denoising effect than several classical and state-of-the-art methods such as NLM and WNNM. Similarly, ACEHP method can keep noise level low while enhancing myocardial regions better than several classical and state-of-the-art methods such as CLAHE and SVDDWT. Furthermore, in the volume rendering after the combined "4D-NLM+ACEHP" processing, the cardiac lumen is clear and the boundary is neat. The Entropy value that can be achieved by our method framework (4D-NLM+ACEHP) is 4.84.
Our new framework can thus provide important improvements to clinical fetal heart ultrasound images.
人类胎儿心脏的四维超声图像对于诸如评估胎儿心脏功能和先天性心脏病早期诊断等医学应用非常重要。然而，由于胎儿超声图像具有高噪声和低对比度的特点，去噪和增强处理很重要。
本文提出了一种特殊的去噪和增强方法框架。它由一种用于四维胎儿心脏超声图像序列的4D-NLM（非局部均值）去噪方法和一种名为“每个直方图柱自适应裁剪”（ACEHP）的增强方法组成。4D-NLM方法利用相邻图像中的上下文相似信息对目标图像进行去噪，ACEHP方法旨在增强心肌区域以使其与血液区域区分开来。
去噪和增强实验表明，4D-NLM方法比诸如NLM和WNNM等几种经典和最新的方法具有更好的去噪效果。同样，ACEHP方法在保持低噪声水平的同时，比诸如CLAHE和SVDDWT等几种经典和最新的方法能更好地增强心肌区域。此外，在经过“4D-NLM+ACEHP”组合处理后的体绘制中，心脏腔清晰且边界整齐。我们的方法框架（4D-NLM+ACEHP）能够达到的熵值为4.84。
因此，我们的新框架能够为临床胎儿心脏超声图像带来重要改进。
