ToolNet: Holistically-Nested Real-Time Segmentation of Robotic Surgical Tools

Understand

Real-time tool segmentation from endoscopic videos is an essential part of many computer-assisted robotic surgical systems and of critical importance in robotic surgical data science.

• We propose two novel deep learning architectures for automatic segmentation of non-rigid surgical instruments.
• Both methods take advantage of automated deep-learning-based multi-scale feature extraction while trying to maintain an accurate segmentation quality at all resolutions.
• The two proposed methods encode the multi-scale constraint inside the network architecture.