论文标题
机器视觉可以为淋巴组织病理学图像分析做什么：全面评论
What Can Machine Vision Do for Lymphatic Histopathology Image Analysis: A Comprehensive Review
论文作者
论文摘要
在过去的十年中，机器视觉（MV）的计算能力得到了不断改进，并且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，MV算法可以为医生提供诊断参考。特别是，深度学习算法的持续改进进一步提高了MV在疾病检测和诊断中的准确性。本文回顾了近年来基于MV基于MV的图像处理技术的应用，包括分割，分类和检测。最后，分析了当前的方法，提出了更多潜在的方法，并进行了更多的前景。
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.
