论文标题
乳房组织病理学图像分析的全面综述，使用经典和深神经网络
A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks
论文作者
论文摘要
乳腺癌是女性中最常见，最致命的癌症之一。由于组织病理学图像包含足够的表型信息，因此它们在乳腺癌的诊断和治疗中起着必不可少的作用。为了提高乳房组织病理学图像分析（BHIA）的准确性和客观性，人工神经网络（ANN）方法被广泛用于乳腺组织病理学图像的分割和分类任务中。在这篇评论中，我们介绍了基于ANN的BHIA技术的全面概述。首先，我们将BHIA系统分为经典和深层神经网络进行深入研究。然后，提出了基于BHIA系统的相关研究。之后，我们分析现有模型以发现最合适的算法。最后，为未来的研究人员提供了方便的方便，可公开访问的数据集以及其下载链接。
Breast cancer is one of the most common and deadliest cancers among women. Since histopathological images contain sufficient phenotypic information, they play an indispensable role in the diagnosis and treatment of breast cancers. To improve the accuracy and objectivity of Breast Histopathological Image Analysis (BHIA), Artificial Neural Network (ANN) approaches are widely used in the segmentation and classification tasks of breast histopathological images. In this review, we present a comprehensive overview of the BHIA techniques based on ANNs. First of all, we categorize the BHIA systems into classical and deep neural networks for in-depth investigation. Then, the relevant studies based on BHIA systems are presented. After that, we analyze the existing models to discover the most suitable algorithms. Finally, publicly accessible datasets, along with their download links, are provided for the convenience of future researchers.
