Prediction of microsatellite instability for the detection of colorectal cancer by GAN-CNN

Khouloud Mnassri, Ines Rahmany, Nawres Khlifa, Sihem Hmissa, Nabiha Missaoui

Abstract: Colorectal cancer (CRC) is a leading cause of mortality worldwide. Microsatellite instability (MSI) detection is crucial for clinical decision-making in CRC, where people with varied therapeutic responses and prognoses are identified by their MSI status. However, the process of MSI detection is very sensitive, as it requires a lot of time, money as well as expertise from pathologists. Thus, we propose in this paper a deep learning approach for MSI detection from histopathological H&E stained whole slide images based on GAN-CNN. The achieved results are very promising and demonstrate the robustness of our approach. The proposed method provides a valuable second opinion to the pathologists and reduces their effort to get the most correct result.