In recent years, with the advancement of computer-aided diagnosis (CAD) technology and whole slide image (WSI), histopathological WSI has gradually played a crucial aspect in the diagnosis and analysis of diseases. To increase the objectivity and accuracy of pathologists' work, artificial neural network (ANN) methods have been generally needed in the segmentation, classification, and detection of histopathological WSI. In this paper, WSI analysis methods based on ANN are reviewed. Firstly, the development status of WSI and ANN methods is introduced. Secondly, we summarize the common ANN methods. Next, we discuss publicly available WSI datasets and evaluation metrics. These ANN architectures for WSI processing are divided into classical neural networks and deep neural networks (DNNs) and then analyzed. Finally, the application prospect of the analytical method in this field is discussed. The important potential method is Visual Transformers.
翻译:近年来,随着计算机辅助诊断(CAD)技术和整个幻灯片图象的进步,组织病理学世界科学倡议在疾病诊断和分析中逐渐发挥关键的作用,为了提高病理学家工作的客观性和准确性,一般需要人工神经网络(ANN)方法来分类、分类和检测病理世界科学倡议(ANN)。本文审查了以ANN为基础的世界科学倡议分析方法。首先,介绍了世界科学倡议和ANN方法的发展状况。第二,我们总结了共同的ANN方法。接着,我们讨论了公开提供的WSI数据集和评估指标。这些用于处理世界科学倡议的ANN结构分为古典神经网络和深神经网络(DNNS),然后进行了分析。最后,讨论了分析方法在这一领域的应用前景。重要的潜在方法是视觉变换器。