A cognitive virtual microscopic framework for knowledge-based exploration of large microscopic images in breast cancer histopathology.

Histopathological examination is a powerful method for prognosis of major diseases such as breast cancer. Analysis of medical images largely remains the work of human experts. Current virtual microscope systems are mainly an emulation of real microscopes with annotation and some image analysis capabilities.

Automatic breast cancer grading of histopathological images.

Breast cancer grading of histopathological images is the standard clinical practice for the diagnosis and prognosis of breast cancer development. In a large hospital, a pathologist typically handles 100 grading cases per day, each consisting of about 2000 image frames. It is, therefore, a very tedious and time-consuming task.