In this study, we developed a CNN model to automatically classify tumor cells, stromal cells, and lymphocytes for lung adenocarcinoma (ADC) pathology images.
The analysis pipeline developed in this study could convert the pathology image into a "spatial map" of tumor cells, stromal cells and lymphocytes.
Methods: In this study, we developed an automated cell type classification pipeline, ConvPath, which includes nuclei segmentation, convolutional neural network- ...
ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network · 74 Citations · 62 References.
An automated cell type classification pipeline, ConvPath, which includes nuclei segmentation, convolutional neural network-based tumor, stromal and lymphocytes ...
Oct 8, 2018 · In this study, we developed an automated cell type classification pipeline, ConvPath, which includes nuclei segmentation, convolutional neural ...
ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network. EBioMedicine. 2019 Dec; 50:103- ...
ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network. https://doi.org/10.1016/j ...
Digital pathological image analysis aided by convolutional neural network predicts prognosis of lung adenocarcinoma patients.
ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network. (2019) EBioMedicine. [Link].
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