… an overview of image analysis methods that have been proposed for breast cancer
histopathology images. We focus on automatic image analysis of histopathology tissue preparations …

… cancer WSIs through the use of both UNet and SegNet models. We introduce a multi-step
training strategy as a remedy for the sparse annotation of histopathological images… we analyze …

… images automatically. Therefore, we introduce it to analyze histopathological images of breast
cancer via … -class issues of breast cancer histopathological image classification by utilizing …

… applied to predict breast cancer recurrence rates. This study … , analysis of stained images,
and a prognosis for cancer patients. … is to analyse whole slide images for the content imaging …

… analysis shows that LDA classifier outperforms over others with 100% and 80% correct
classification rate for the nonmalignant Vs malignant breast histopathology images respectively. …

… histopathology images is large and the size of the images is also large. Currently, automated
image analysis system for histopathology images … of cancer, (2) the histological subtype of a …

… In this review, we investigate the computational steps to automatically diagnose cancer
by making use of histopathological images. There are primarily three steps: preprocessing, …

The analysis of histological images is based on visual assessment of tissues by specialists
using an optical microscopy. This task can be time-consuming and challenging, mainly due to …

… Our research work combines image … histopathological images (HI) and finds the optimal
algorithm to identify disease early. To do so, we did analysis on breast cancer HI images. Breast …

… In this bibliometric analysis, we discovered that deep learning algorithms can be utilized to
classify breast cancer histopathology images, given that the model performance (in terms of …