Open AccessReal‐time surgical instrument tracking in robot‐assisted surgery using multi‐domain convolutional neural network
Author(s) -
Qiu Liang,
Li Changsheng,
Ren Hongliang
Publication year - 2019
Publication title -
healthcare technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.45
H-Index - 19
ISSN - 2053-3713
DOI - 10.1049/htl.2019.0068
Subject(s) - computer science , surgical instrument , convolutional neural network , bittorrent tracker , haptic technology , robot , artificial intelligence , surgical robot , tracking (education) , computer vision , domain (mathematical analysis) , eye tracking , simulation , surgery , medicine , psychology , mathematical analysis , pedagogy , mathematics
Image‐based surgical instrument tracking in robot‐assisted surgery is an active and challenging research area. Having a real‐time knowledge of surgical instrument location is an essential part of a computer‐assisted intervention system. Tracking can be used as visual feedback for servo control of a surgical robot or transformed as haptic feedback for surgeon–robot interaction. In this Letter, the authors apply a multi‐domain convolutional neural network for fast 2D surgical instrument tracking considering the application for multiple surgical tools and use a focal loss to decrease the effect of easy negative examples. They further introduce a new dataset based on m2cai16‐tool and their cadaver experiments due to the lack of established public surgical tool tracking dataset despite significant progress in this field. Their method is evaluated on the introduced dataset and outperforms the state‐of‐the‐art real‐time trackers.