Abstract
Of an order of 330 million surgeries are performed worldwide every year.
Yet there is a backlog of around 150 million pending surgeries annually.
Surgical robotics is becoming a lot more sophisticated by the day. Much
of this increasing success is due to advances in Computer Vision (CV) .
CV allows the tracking of tools, detection of organs, and a description
of the phase of surgery that enables a surgeon to perform the delicate
art of surgery with much greater precision and efficiency. These
advancements have also enabled remote robotic surgery in which a patient
and the surgeon can be far apart from each other geographically.
In this paper, we report promising results of evolving the architecture
of capsule networks for tool classification for Computer-Aided
Laparoscopy (CAL).