graviti
产品服务
解决方案
知识库
公开数据集
关于我们
Cholec80
许可协议: Unknown

Overview

The Cholec80 dataset contains 80 videos of cholecystectomy surgeries performed by 13 surgeons. The videos are captured at 25 fps. The dataset is labeled with the phase (at 25 fps) and tool presence annotations (at 1 fps). The phases have been defined by a senior surgeon in our partner hospital. Since the tools are sometimes hardly visible in the images and thus difficult to be recognized visually, we define a tool as present in an image if at least half of the tool tip is visible.This dataset has been released. If you wish to have access to this dataset, please kindly fill the request form.This dataset is associated with the publication [Twinanda:TMI2016]. If you use this data, you are kindly requested to cite the work that led to the generation of this dataset:A.P. Twinanda, S. Shehata, D. Mutter, J. Marescaux, M. de Mathelin, N. Padoy, EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos, IEEE Transactions on Medical Imaging (TMI), to appear (arXiv preprint), doi:10.1109/TMI.2016.2593957, 2016

数据概要
数据格式
video,
数据量
--
文件大小
--
| 数据量 -- | 大小 --
Cholec80
许可协议: Unknown

Overview

The Cholec80 dataset contains 80 videos of cholecystectomy surgeries performed by 13 surgeons. The videos are captured at 25 fps. The dataset is labeled with the phase (at 25 fps) and tool presence annotations (at 1 fps). The phases have been defined by a senior surgeon in our partner hospital. Since the tools are sometimes hardly visible in the images and thus difficult to be recognized visually, we define a tool as present in an image if at least half of the tool tip is visible.This dataset has been released. If you wish to have access to this dataset, please kindly fill the request form.This dataset is associated with the publication [Twinanda:TMI2016]. If you use this data, you are kindly requested to cite the work that led to the generation of this dataset:A.P. Twinanda, S. Shehata, D. Mutter, J. Marescaux, M. de Mathelin, N. Padoy, EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos, IEEE Transactions on Medical Imaging (TMI), to appear (arXiv preprint), doi:10.1109/TMI.2016.2593957, 2016

0
立即开始构建AI
graviti
wechat-QR
长按保存识别二维码,关注Graviti公众号

Copyright@Graviti
沪ICP备19019574号
沪公网安备 31011002004865号