Journal paper accepted in Computing and Informatics

Our paper on “Breast Histopathology with High-Performance Computing and Deep Learning” (M. Graziani et. al) has been accepted for publication in Computing and Informatics, in the special issue on Providing Computing Solutions for Exascale Challenges.

In this work, we present our modular pipeline for detecting tumorous regions in digital specimens of breast lymph nodes with deep learning models. We evaluate challenges and benefits of training models on high-performance and cloud computing with millions of images.

Overview of the proposed CamNet software