随着科学技术的不断发展, 医学诊断技术也在不断的进步之中, 超声技术作为一种医学诊断手段已广泛地应用于各个医疗领域, 并且由于对人体的无害性以及能够动态且清晰地展现人体组织和器官的健康状态从而普遍得到了医生和患者的认可. 在超声技术的不断发展中, 人们对超声实时成像质量上的要求显著提高, 由于超声探头的材质例如陶瓷换能器制造的局限性以及在降低成本及帧速率等原因而采用的低通道扫描的折中方案所造成的噪点和伪影会遮挡人体组织和器官的有用信息从而严重影响医生的辅助诊断, 在超声领域如何进行图像及视频的增强和伪影的抑制成为一个重要的挑战. 本文首先描述了几种空间域抑制伪影的滤波算法及其局限性, 并提出了一种基于频率域的伪影抑制算法, 该算法能够良好的抑制在超声实时成像中的周期性伪影, 本文先通过正弦波模拟周期性伪影实验以突显其在频率域上的特性, 然后将超声图像进行二维傅立叶变换到频率域来对这些伪影进行抑制, 由于这些伪影具有周期性, 所以在频率域上具有明显的特征, 本文通过滑动窗口扫描结合阈值的算法模型找出频率域上对应这些伪影的集合, 然后根据频域的动态范围及给定的阈值来对集合中的这些疑似伪影的点进行压低处理, 再通过反傅立叶变换将超声图像变换到空间域上来从而得到处理后的图像. 通过这种方法, 能够提高超声图像对周期性伪影抑制且保留有用的信息, 能够提高医生对人体器官状况的判断结果的准确性.
With the continuous development of science and technology, medical diagnosis technology also makes continuous progress. Ultrasound technology, as a means of medical diagnosis, has been widely used in various medical fields. It has been widely recognized by doctors and patients because it is harmless to the human body and can dynamically and clearly show the health state of human tissues and organs. With the continuous development of ultrasound technology, people have higher requirements for the quality of ultrasound imaging. Due to the limitations of the materials of ultrasonic probes, such as for the manufacturing of ceramic transducer, and the compromise scheme of low-channel scanning adopted to reduce the cost and frame rate, the caused noises and artifacts will block the useful information of human tissues and organs, which will seriously affect doctors’ auxiliary diagnosis. In the field of ultrasound, how to enhance images and videos and suppress artifacts has become an important challenge. This study describes several filtering algorithms for artifact suppression in the spatial domain and their limitations and proposes an artifact suppression algorithm based on the frequency domain, which can well suppress the periodic artifact in real-time ultrasonic imaging. Firstly, this study simulates the periodic artifact with a sine wave to highlight its characteristics in the frequency domain. Then, the ultrasonic image is subjected to a two-dimensional Fourier transform into the frequency domain to suppress these artifacts. Because these artifacts are periodic, they have obvious characteristics in the frequency domain. The set corresponding to these artifacts in the frequency domain is found through the algorithm model of sliding window scanning combined with a threshold. Next, according to the dynamic range of the frequency domain and the given threshold, the points of these suspected artifacts in the set are depressed. Finally, the ultrasonic image is transformed into the spatial domain by inverse Fourier transform to obtain the processed image. This method can improve the suppression of periodic artifacts in ultrasonic images and retain useful information, thus able to enhance the accuracy of doctors’ judgment regarding human organ conditions.