The normal symptoms of breast cancer are masses or lumps that feel different from the other tissues, and there are two types of masses- benign and malignant. Benign masses are abnormal growths which are not cancerous, whereas malignant masses are cancerous. Various methods have been proposed ...
A dataset for breast cancer histopathological image classification. IEEE Trans. Biomed. Eng. 63, 1455–1462 (2015). Article PubMed Google Scholar Aresta, G. et al. Bach: Grand challenge on breast cancer histology images. Med. Image Anal. 56, 122–139 (2019). Article PubMed Google ...
Classification of breast cancer histology images using transfer learning 一、数据集: BACH 2018 grand challenge (ICIAR 2018 Grand Challenge on BreAst Cancer Histology images) iciar2018-challenge.grand-challenge.org 其实算得上Camelyon 16和17 的后继版本。 所不同的是,camelyon 16的数据只有WSI(whole...
Automated breast cancer multi-classification from histopathological images plays a key role in computer-aided breast cancer diagnosis or prognosis. Breast cancer multi-classification is to identify subordinate classes of breast cancer (Ductal carcinoma,
Breast cancer histology imagesCNNimage classificationThe paper employs deep learning to classify breast cancer histopathological image into normal, benign and malignant subclasses in situ carcinoma and invasivecarcinoma categories. The classification is mainly based on cells' density, variability, and organizat...
Rakhlin A, Shvets A, Iglovikov V, Kalinin AA (2018) Deep convolutional neural networks for breast cancer histology image analysis. In: International Conference Image Analysis and Recognition, Springer pp 737–744 Khan AM, Rajpoot N, Treanor D, Magee, (2014) A nonlinear mapping approach to st...
Mitosis detection in breast cancer histology images via deep cascaded networks. In: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 1160–1166, 2016. Roullier, V., Lezoray, O., Ta, V.T., and Elmoataz, A., Multi-resolution graph-based analysis of histopathological ...
Araújo, T. et al. Classification of breast cancer histology images using convolutional neural networks.PLoS ONE12, e0177544 (2017). ArticleGoogle Scholar Jannesari, M. et al. Breast cancer histopathological image classification: a deep learning approach. In2018 IEEE International Conference on Bioinf...
In breast cancer, several gene expression assays have been developed to provide a more personalised treatment. This study focuses on the prediction of two molecular proliferation signatures: an 11-gene proliferation score and the MKI67 proliferation marker gene. The aim was to assess whether these ...
Colorectal cancer (CRC) is the second most common cause of cancer death in the United States, accounting for nearly 53,000 deaths annually1. Histopathologic evaluation remains a cornerstone for diagnosing and staging CRC, and the histology subtypes and genetic variations are the keys to treatment ...