Paper Info
Title
Robust Mosaicing of Endomicroscopic Videos via Context-Weighted Correlation Ratio
Abstract
Probe-based confocal laser endomicroscopy (pCLE) is a promising imaging tool that provides in situ and in vivo optical imaging to perform real-time pathological assessments. However, due to limited field of view, it is difficult for clinicians to get a full understanding of the scanned tissues. In this paper, we develop a novel mosaicing framework to assemble all frame sequences into a full view image. First, a hybrid rigid registration that combines feature matching and template matching is presented to achieve a global alignment of all frames. Then, the parametric free-form deformation (FFD) model with a multiresolution architecture is implemented to accommodate non-rigid tissue distortions. More importantly, we devise a robust similarity metric called context-weighted correlation ratio (CWCR) to promote registration accuracy, where spatial and geometric contexts are incorporated into the estimation of functional intensity dependence. Experiments on both robotic setup and manual manipulation have demonstrated that the proposed scheme significantly precedes some state-of-the-art mosaicing schemes in the presence of intensity fluctuations, insufficient overlap and tissue distortions. Moreover, the comparisons of the proposed CWCR metric and two other metrics have validated the effectiveness of the context-weighted strategy in quantifying the differences between two frames. Benefiting from more rational and delicate mosaics, the proposed scheme is more suitable to instruct diagnosis and treatment during optical biopsies.
Year
DOI
Venue
2021
10.1109/TBME.2020.3007768
IEEE Transactions on Biomedical Engineering
Keywords
DocType
Volume
Endoscopy,Microscopy,Robotics
Journal
68
Issue
ISSN
Citations 
2
0018-9294
1
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Lun Gong110.68
Jian Zheng2387.92
Zhongyuan Ping310.34
Yifan Wang410.34
Shuxin Wang54411.24
Siyang Zuo6177.12