Nahid: AI-based Algorithm for operating fully-automatic surgery

TL;DR

This paper introduces Nahid, an AI-based algorithm that automates ovarian endometriosis surgery using computer vision, specifically training a U-net model for real-time diagnosis and treatment during surgery.

Contribution

The paper presents the first fully automated surgical method utilizing AI and computer vision, with a focus on ovarian endometriosis diagnosis and treatment.

Findings

U-net trained to detect endometriosis during surgery

Automated diagnosis and treatment of ovarian endometriosis

Discussion of advantages and challenges of surgical automation

Abstract

In this paper, for the first time, a method is presented that can provide a fully automated surgery based on software and computer vision techniques. Then, the advantages and challenges of computerization of medical surgery are examined. Finally, the surgery related to isolated ovarian endometriosis disease has been examined, and based on the presented method, a more detailed algorithm is presented that is capable of automatically diagnosing and treating this disease during surgery as proof of our proposed method where a U-net is trained to detect the endometriosis during surgery.