With the increasing ability to routinely and rapidly digitize whole slide images with slide
scanners, there has been interest in developing computerized image analysis algorithms for …

This paper presents a deep learning approach for automatic detection and visual analysis of
invasive ductal carcinoma (IDC) tissue regions in whole slide images (WSI) of breast cancer …

Advances in artificial intelligence technologies have made it possible to obtain more
accurate and reliable results using digital images. Due to the advances in digital …

Background: Metastasis is the main cause of death toll among breast cancer patients. Since
current approaches for diagnosis of lymph node metastases are time-consuming, deep …

The gold standard for breast cancer diagnosis, treatment, and management is the
histological analysis of a suspected section. Histopathology consists in analyzing the …

Accurately identifying and categorizing cancer structures/sub-types in histological images is
an important clinical task involving a considerable workload and a specific subspecialty of …

Breast cancer is the most commonly diagnosed cancer and registers the highest number of
deaths for women. Advances in diagnostic activities combined with large-scale screening …

Currently, histopathological tissue examination by a pathologist represents the gold
standard for breast lesion diagnostics. Automated classification of histopathological whole …

Invasive ductal carcinoma (IDC) breast cancer is a significant health concern for women all
around the world and early detection of the disease may increase the survival rate in …

Advances in the quality of whole-slide images have set the stage for the clinical use of digital
images in anatomic pathology. Along with advances in computer image analysis, this raises …