More specifically, we systematically study two recent milestones of CNNs, i.e., VggNet and ResNet, for breast cancer histopathological image classification. Considering large variety among within-class images, we adopt larger patches of the original image as the input of network to combine...
In this work, we propose a breast cancer histopathology image classification by assembling multiple compact Convolutional Neural Networks (CNNs). First, a hybrid CNN architecture is designed, which contains a global model branch and a local model branch. By local voting and two-branch information m...
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...
Mammogram is important and effective in breast cancer diagnosis. The Radiologist must analyze visually, based on his expertise, to determine whether it is cancer or not. We explore the use of CEP for breast cancer image classification and information enrichment. The results reveal that the ...
Deep learning has been used extensively in histopathological image classification, but people in this field are still exploring new neural network architectures for more effective and efficient cancer diagnosis. Here, we propose multi-scale, multi-view p
关键词: deep learning breast cancer image classification spatial pyramid pooling global average pooling 会议名称: 2019 10th International Conference on Information Technology in Medicine and Education (ITME) 会议时间: 23 January 2020 主办单位: IEEE ...
“Deep features for breast cancer histopathological image classification,” in Proc. IEEE Int. Conf. Syst., Man, Cybern. (SMC), Oct. 2017, pp. 1868–1873. [6] Z. Han, B. Wei, Y . Zheng, Y . Yin, K. Li, and S. Li, “Breast cancer ...
Breast cancer is a common malignancy and a leading cause of cancer-related deaths in women worldwide. Its early diagnosis can significantly reduce the morbidity and mortality rates in women. To this end, histopathological diagnosis is usually followed as
B. “Histopathological image analysis: a review. Biomedical Engineering,” IEEE Reviews in. 2009;2:147-71. [7] F. Spanhol; L. Oliveira; C. Petitjean; L. Heutte, “A Dataset for Breast Cancer Histopathological Image Classification,” in IEEE Transactions on ...
Chasing a Better Decision Margin for Discriminative Histopathological Breast Cancer Image Classification Rigorous experimentation on a well-established histopathological breast cancer image dataset, BreakHis, has been conducted. As per the results, it is evident... P Alirezazadeh,F Dornaika,A Moujahid - ...