In the past ten years, the computing power of machine vision (MV) has been continuously improved, and image analysis algorithms have developed rapidly. At the same time, histopathological slices can be stored as digital images. Therefore, MV algorithms can provide doctors with diagnostic references. In particular, the continuous improvement of deep learning algorithms has further improved the accuracy of MV in disease detection and diagnosis. This paper reviews the applications of image processing technology based on MV in lymphoma histopathological images in recent years, including segmentation, classification and detection. Finally, the current methods are analyzed, some more potential methods are proposed, and further prospects are made.
翻译：近十年来,机器视力的计算能力不断提高,图像分析算法迅速发展,同时,组织病理学切片可以作为数字图像存储,因此,组织病理学切片可以向医生提供诊断参考,特别是不断改进深层次学习算法进一步提高了疾病检测和诊断中MV的准确性,本文回顾了近年来基于淋巴瘤组织病理学图像MV的图像处理技术的应用情况,包括分解、分类和检测。最后,对目前的方法进行了分析,提出了一些可能的方法,并提出了进一步的前景。
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