We demonstrated the ability of transfer learning in comparison with the fully-trained network on the histopathological imaging modality by considering three pre-trained networks: VGG16, VGG19, and ResNet50 and analyzed their behavior for magnification independent breast cancer classification. Concurrently,...
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
模型数量 2 乳腺癌检测 任务数量 2 模型收录中 可用模型 选择基准,对比模型表现 模型名模型规模最佳表现情况技术方法发布时间适配资源 HarmoFL- ON Camelyon17 2021 SOTA! Accuracy 96.17 -2021-12 PyTorch GPU CPU CUDA 查看项目 XBNET- ON Breast cancer Wisconsin_class 4 ...
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...
Two important challenges are left open in the existing breast cancer histopathology image classification: The adopted deep learning methods usually design a patch-level CNN, and put the downsampled whole cancer image into the model directly. However, due to the information loss introduced by the dow...
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
Microscopic histology image analysis is a cornerstone in early detection of breast cancer. However these images are very large and man- ual analysis is error prone and very time consuming. Thus automating this process is in high demand. We proposed a hierarchical system of con- volutional neural...
Deep convolutional neural networks for breast cancer histology image analysis. arXiv:1802.00752v2, 2018. Öztürk S, Akdemir B. HIC-net: a deep convolutional neural network model for classification of histopathological breast images. Comput Elect Eng. 2019;76:299–310. Article Google Scholar ...
Classification of Breast Cancer Based on Histology Images Using Convolutional Neural Networks IEEE Access, 6 (2018), pp. 24680-24693 CrossrefView in ScopusGoogle Scholar 10 N. Bayramoglu, J. Kannala and J. Heikkilä, "Deep learning for magnification independent brea...
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,