… To validate our method, we apply it to two datasets of H&E stained histopathology images
for nuclei segmentation and compare the results with fully supervised methods, including the …

… based method for detection of lung cancer in whole slide histopathology images. VGG16 and
… have potential to perform lung cancer diagnose from whole slide images, but more effort is …

… Hence, we segmented them into tiles with a 512 × 512 pixel size from the 110 H&E … deep
learning of histopathological imaging features can predict the prognosis of lung cancer patients, …

… cell detection and segmentation algorithm for pathological images. The … and segmentation
of cell nuclei in histopathology images. … in histological imagery. IEEE Transactions on Medical …

… (H&E) stained histopathological images using contrastive clustering … potential of utilizing
histopathology images-based deep … a Segmentation of tumor regions in the whole slide image (…

… Finally, the classification result of the testing image is decided by the … in histopathological
image analysis. In the following sections, we introduce the details of robust cell segmentation …

… HookNet in two histopathology image segmentation tasks where … segmentation in breast
cancer and, (2) segmentation of tertiary lymphoid structures and germinal centers in lung cancer…

… lung cancer is H&E. A surgical pathologist with a sub-specialty expertise in pulmonary pathology
analyzed the digitized H&E histological images (… ) were used to generate image masks …

… key components to discern cancer type. The … lung as well as adenocarcinomas of colon
using convolutional neural networks by evaluating the digital pathology images for these cancers…

… for image-related tasks including classification, segmentation, medical … lung histopathology
images. This dataset is obtained from LC25000 Lung and colon histopathological image …