9 May 2017 · We present context-aware stacked convolutional neural networks (CNN) for classification of breast WSIs into normal/benign, DCIS, and invasive ductal carcinoma ...
10 May 2017 · In this paper, we present context-aware stacked convolutional neural networks (CNN) for classification of breast WSIs into normal/benign, ductal carcinoma in ...
A context-aware stacked convolutional neural networks (CNN) for classification of breast WSIs into normal/benign, DCIS, and invasive ductal carcinoma (IDC) ...
12 May 2017 · In this paper, we present context-aware stacked convolutional neural networks (CNN) for classification of breast WSIs into normal/benign, ductal ...
In this work, we consider diagnostic re- gions captured from CRC histology images containing enough context to reliably predict the cancer grade (see Figure 1).
22 Jul 2019 · This work proposes a hybrid context-aware convolutional neural network with recurrent neural network (CA-CNN-RNN) based on skin cancer histology images.
Using deep convolutional neural networks, we trained an algorithm to discriminate between stroma surrounding invasive cancer and stroma from benign biopsies.
Convolutional neural networks (CNNs) have been recently used for a variety of histology image analysis. However, availability of a large dataset is a major ...
Convolutional neural networks (CNNs) have been recently used for a variety of histology image analysis.
Missing: stacked whole- slide
This paper proposes a novel network WSI-Net for segmentation and classification of gigapixel breast whole-slide images (WSIs).