Paper Info
Title
Robotically Surgical Vessel Localization Using Robust Hybrid Video Motion Magnification
Abstract
Vessel and neurovascular bundle localization plays an essential role in endoscopic and robotic surgery. It still remains challenging to spare vessels and neurovascular bundles to avoid inadvertent injury due to limited visual and tactile perception of surgeons. This work assumes that surgeons have great difficulty in intuitively perceiving small pulsatile motion of vessels and neurovascular bundles from complex surgical field provided by endoscopic videos, and proposes a new surgical video pulsatile motion magnification method to help surgeons easily and precisely recognize vessels or neurovascular bundles by their visual systems. The new method consists of robust hybrid temporal filtering and deeply learned spatial decomposition. The proposed hybrid temporal filtering can significantly magnify pulsatile motion more consistent with reality and simultaneously keep non-pulsating regions in magnified videos almost identical to original videos, and learning-based spatial decomposition can reduce noise and ring artifacts in magnified videos. We evaluate our method on surgical videos acquired from robotic prostatectomy, with the experimental results showing that our method essentially outperforms current motion magnification approaches. In particular, visual quality and quantitative assessment of our method are certainly better than these methods.
Year
DOI
Venue
2021
10.1109/LRA.2021.3058906
IEEE ROBOTICS AND AUTOMATION LETTERS
Keywords
DocType
Volume
Surgical robotics, laparoscopy, computer vision for medical robotics, vessel localization, motion magnification, hybrid temporal filtering
Journal
6
Issue
ISSN
Citations 
2
2377-3766
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Wenkang Fan101.35
Zhuohui Zheng200.68
Wankang Zeng301.35
Yinran Chen401.35
Hui-Qing Zeng501.69
Hong Shi600.34
Xiongbiao Luo712422.22