來源紀錄
Recognizing surgical phases in laparoscopic video
已發表論文
此語言的正文尚未翻譯，暫以英文顯示。
The source is Twinanda and colleagues, arXiv:1602.03012, posted 9 February 2016. It introduces EndoNet, a research network for phase and instrument recognition on laparoscopic cholecystectomy video, demonstrated on the public Cholec80 collection. The paper is about whether a model can tell where a case is in its sequence. This index does not restate the research metrics as clinical outcomes and does not treat the work as a cleared intraoperative product.
- 來源日期
- 2016年2月9日 · 年份 2016
- 證據標籤
- 已發表
- 來源類型
- 論文
完整引用
Twinanda et al., arXiv:1602.03012
Twinanda et al. EndoNet: a deep architecture for recognition tasks on laparoscopic videos. arXiv:1602.03012, 9 February 2016. https://arxiv.org/abs/1602.03012
已公開的關鍵事實
- EndoNet is a research network for phase and tool recognition in laparoscopic cholecystectomy video.
- The demonstration collection is the public Cholec80 set.
- The linked source is the arXiv preprint dated 9 February 2016.
- The paper reports recognition performance. Those figures are not restated here as clinical outcomes.
- The entry is not a live operating-room advisory and not a cleared device.
供教育和市場掃描的目錄條目。不是醫療建議，也不是背書。