Offers a method for discriminating microscopic cancerous imaging. The approach provides a generic computer-aided diagnosis (CAD) framework that consists of two main models: Inception and ResNet. The program permits users to classify cancer types and breast cancer sub-types from histopathological images derived from Hematoxylin and eosin stain (H&E) and Immunohistochemistry (IHC) slides. It also supplies additional techniques for data augmentation and advanced pre-processing.
Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran; Department of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran; Englander Institute for Precision Medicine, The Meyer Cancer Center, Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine of Cornell University, NY, USA
MotlaghEtAl2018 funding source(s)
Supported in part by the Iranian National Elite Foundation and grants provided by Royan Institute and a start-up fund from Weill Cornell Medicine.