Politehnica University of Timişoara, Timişoara, Romania.
Stud Health Technol Inform. 2023 Jun 29;305:14-17. doi: 10.3233/SHTI230411.
Digital Pathology is an area that could benefit a lot from the automatic classification of scanned microscopic slides. One of the main problems with this is that the experts need to understand and trust the decisions of the system. This paper is an overview of the current state of the art methods used in histopathological practice for explaining CNN classification useful for histopathological experts and ML engineers that work with histopathological images. This paper is an overview of the current state of the art methods used in the histopathological practice for explain. The search was performed using SCOPUS database and revealed that there are few applications of CNNs for digital pathology. The 4-term search yielded 99 results. This research sheds light on the main methods that can be used for histopathology classification and offers a good starting point for future works.
数字病理学是一个可以从扫描显微镜载玻片的自动分类中受益良多的领域。其中一个主要问题是，专家需要理解和信任系统的决策。本文综述了当前在组织病理学实践中用于解释 CNN 分类的最新方法，这些方法对从事组织病理学图像工作的组织病理学专家和 ML 工程师很有用。本文综述了当前在组织病理学实践中用于解释 CNN 分类的最新方法。搜索使用了 SCOPUS 数据库，结果表明，CNN 在数字病理学中的应用较少。4 项术语搜索得到了 99 个结果。这项研究阐明了可用于组织病理学分类的主要方法，并为未来的工作提供了一个良好的起点。
