论文标题
ISINET：一种基于实例的手术仪器分割的方法
ISINet: An Instance-Based Approach for Surgical Instrument Segmentation
论文作者
论文摘要
我们研究机器人辅助手术场景中手术仪器的语义分割的任务。我们提出了基于实例的外科手术仪器分割网络（ISINET），该方法从基于实例的分割角度来解决此任务。我们的方法包括一个时间一致性模块，该模块考虑了该问题的先前被忽略的固有时间信息。我们在现有的基准测试中验证了该任务的方法，内窥镜视觉2017机器人仪器分割数据集以及2018年版本的数据集，我们为仪器细分的细粒度版本扩展了其注释。我们的结果表明，Isinet的表现明显优于最先进的方法，我们的基线版本重复了以前方法的交叉点（IOU），并且我们完整的模型对IOU进行了三式三式“ iou”。
We study the task of semantic segmentation of surgical instruments in robotic-assisted surgery scenes. We propose the Instance-based Surgical Instrument Segmentation Network (ISINet), a method that addresses this task from an instance-based segmentation perspective. Our method includes a temporal consistency module that takes into account the previously overlooked and inherent temporal information of the problem. We validate our approach on the existing benchmark for the task, the Endoscopic Vision 2017 Robotic Instrument Segmentation Dataset, and on the 2018 version of the dataset, whose annotations we extended for the fine-grained version of instrument segmentation. Our results show that ISINet significantly outperforms state-of-the-art methods, with our baseline version duplicating the Intersection over Union (IoU) of previous methods and our complete model triplicating the IoU.
