Histotyping - developed by ICGI
ICGI has developed Histotyping, a fully automated histological characterisation of H & E-stained sections from cancer specimens for prognostic purposes. The method is based on deep learning by convolutional neural networks trained on images of H & E-stained tissue sections. The patient outcome is used to guide the training process into a system that can identify tissue patterns in the HE-sections that are distinct for patient prognosis. The resulting computer model can be applied to a new patient’s tumour sample and estimates the probability of a good or poor patient outcome.
