Abstract:

Ultrasound images provide important auxiliary information for clinical disease detection and diagnosis. The application of machine learning in ultrasound images has brought new changes to the analysis and diagnosis of ultrasound images. This paper first introduces the research status of ultrasound images from the aspects of denoising, segmentation, detection and classification of ultrasound images, and then summarizes the research and application progress of machine learning algorithms in the field of ultrasound images in recent years. Finally, this paper points out the difficulties and challenges faced by the research institute in the field of medical imaging based on machine learning, and looks forward to the future research direction, in order to provide reference and research ideas for further research and application of machine learning in the field of medical imaging.

Key words: ultrasound image, machine learning, deep learning, transfer learning

摘要：

超声图像为临床疾病检测与诊断提供重要的辅助信息，机器学习在超声图像中的应用给超声图像的分析诊断带来了新变革。从超声图像的去噪、分割、检测、分类等方面介绍了超声图像的研究现状。分类综述了近年来机器学习算法在超声图像领域的研究和应用进展。指出了基于机器学习在医学影像领域开展研究所面临的困难与挑战，并对未来研究方向进行了展望，以期为机器学习在医学影像领域的进一步研究与应用提供参考和研究思路。

关键词: 超声图像, 机器学习, 深度学习, 迁移学习