作者
Thibaut Issenhuth, Vinkle Srivastav, Afshin Gangi, Nicolas Padoy
发表日期
2019/6/1
期刊
International journal of computer assisted radiology and surgery
卷号
14
页码范围
1049-1058
出版商
Springer International Publishing
简介
Purpose
Face detection is a needed component for the automatic analysis and assistance of human activities during surgical procedures. Efficient face detection algorithms can indeed help to detect and identify the persons present in the room and also be used to automatically anonymize the data. However, current algorithms trained on natural images do not generalize well to the operating room (OR) images. In this work, we provide a comparison of state-of-the-art face detectors on OR data and also present an approach to train a face detector for the OR by exploiting non-annotated OR images.
Methods
We propose a comparison of six state-of-the-art face detectors on clinical data using multi-view OR faces, a dataset of OR images capturing real surgical activities. We then propose to use self-supervision, a domain adaptation method, for the task of face …
学术搜索中的文章
T Issenhuth, V Srivastav, A Gangi, N Padoy - International journal of computer assisted radiology …, 2019