Using explainable deep learning in da Vinci Xi robot for tumor detection

Abstract

Deep learning has proved successful in computer-aided detection in interpreting ultrasound images, COVID infections, identifying tumors from computed tomography (CT) scans for humans and animals. This paper proposes applications of deep learning in detecting cancerous cells inside patients via laparoscopic camera on da Vinci Xi surgical robots. The paper presents method for detecting tumor via object detection and classification/localizing using GRAD-CAM. Localization means heat map is drawn on the image highlighting the classified class. Analyzing images collected from publicly available partial robotic nephrectomy videos, for object detection, the final mAP was 0.974 and for classification the accuracy was 0.84.