… the applications of CNNs to histopathological images of lung cancer. Furthermore, no public
… on lung cancer detection was only on cytological image [48]. The size of each image was …

… of Segmentation Methods The segmentation of nuclei in cancer histopathology images
can … Similarly, a two-stage segmentation method to obtain cellular structures in high-dimensional …

… 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…

… We evaluate the performance rates of both UNet and SegNet models in a histopathological
image segmentation context. As detailed in Table 6, SegNet enables ≈5% higher accuracy …

… nuclei segmentation framework for histopathology images using … (2) weakly supervised nuclei
segmentation. The goal of the … locations of all nuclei in training images. A challenge is that …

… 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, …

… based segmentation. It also saves the time and effort required for the inspection of histopathology
images … an AI-based nuclear segmentation technique in which an image was first stain-…

… 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…

… tumor cells and stromal cells are often unclear in standard H&E–stained lung cancer pathology
images, we segmented … TIL are mainly white blood cells that have migrated into a tumor …

… and eccentricity from the segmented image region of … lung cancer detection using
histopathological images. A convolutional neural network (CNN) was implemented to classify an …