… diagnosis of lung cancer subtypes, this study included relatively rare lung adenosquamous
… histopathological images of ASC, lung squamous cell carcinoma (LUSC) and small cell lung …

… node involvement on histopathological slides has attracted … images and histopathological
images. The result analysis shows that the detection accuracy is better when histopathological …

… of lung cancer using histopathological images. In this work, the histopathological images …
-based segmentation and the segmented image intensity values were dimensionally reduced …

… a hybrid network for the categorization of lung histopathology images, and it did so by … for
lung nodule sample classification. The LC25000 Lung and colon histopathology image dataset, …

… both classify histologic patterns in lung adenocarcinoma and … images. We first trained a
convolutional neural network to map histologic features across whole slide images of lung cancer …

… Because the classification between LP and AC is directly related to prognosis and survival
of lung cancer [23], we believe that our CAD system is useful for evaluating the prognosis and …

… histopathological image from our dataset consisting of many tumor lesions. The high-resolution
inset images … a subject’s body) on histopathological mouse lung sections is difficult, time …

… In conclusion, our study highlights the potential of utilizing histopathology images-based
deep learning to improve prognostic predictions and therapeutic response evaluation in SCLC. …

… histopathological tissue slides more quickly with digitized WSI. Manual evaluations of massive
histological images are … to classify other cancers like lung cancer, brain tumor and so on. …

… in this study, the highest accuracy to classify lung cancer was gained by ResNet18 with 98.82%
… % accuracy to classify lung cancer and 88.26% accuracy for colon cancer. The proposed …