Breast cancer diagnosis often requires accurate detection of metastasis in lymph nodes
through Whole-slide Images (WSIs). Recent advances in deep convolutional neural …

Metastasis detection of lymph nodes in Whole-slide Images (WSIs) plays a critical role in the
diagnosis of breast cancer. Automatic metastasis detection is a challenging issue due to the …

Lymph node metastasis is one of the most important indicators in breast cancer diagnosis,
that is traditionally observed under the microscope by pathologists. In recent years, with the …

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 …

Simple Summary The assistance of computer image analysis that automatically identifies
tissue or cell types has greatly improved histopathologic interpretation and diagnosis …

Lymph node metastasis is one of the most significant diagnostic indicators in breast cancer,
which is traditionally observed under the microscope by pathologists. In recent years …

Supervised learning methods are commonly applied in medical image analysis. However,
the success of these approaches is highly dependent on the availability of large manually …

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 …

Importance Application of deep learning algorithms to whole-slide pathology images can
potentially improve diagnostic accuracy and efficiency. Objective Assess the performance of …

The frozen section (FS) diagnoses of pathology experts are used in China to determine
whether sentinel lymph nodes of breast cancer have metastasis during operation. Direct …