Kanakatte Aparna, Ramaswamy Akshaya, Gubbi Jayavardhana, Ghose Avik, Purushothaman Balamuralidhar
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:1658-1661. doi: 10.1109/EMBC44109.2020.9176676.
Laparoscopic cholecystectomy surgery is a minimally invasive surgery to remove the gallbladder, where surgical instruments are inserted through small incisions in the abdomen with the help of a laparoscope. Identification of tool presence and precise segmentation of tools from the video is very important in understanding the quality of the surgery and training budding surgeons. Precise segmentation of tools is required to track the tools during real-time surgeries. In this paper, a new pixel-wise instance segmentation algorithm is proposed, which segments and localizes the surgical tool using spatio-temporal deep network. The performance of the proposed has been compared with the state-of-the-art image-based instance segmentation method using the Cholec80 dataset. It is also compared with methods in the literature using frame-level presence detection and spatial detection with good results.
腹腔镜胆囊切除术是一种用于切除胆囊的微创手术，手术器械通过腹部的小切口在腹腔镜的辅助下插入。识别工具的存在并从视频中精确分割出工具对于了解手术质量和培训初出茅庐的外科医生非常重要。在实时手术过程中跟踪工具需要精确分割工具。本文提出了一种新的逐像素实例分割算法，该算法使用时空深度网络对手术工具进行分割和定位。使用Cholec80数据集将所提出算法的性能与基于图像的最新实例分割方法进行了比较。还与文献中使用帧级存在检测和空间检测的方法进行了比较，结果良好。
