Towards scene adaptive image correspondence for placental vasculature mosaic in computer assisted fetoscopic
Liangjing Yang1, Junchen Wang1, Takehiro Ando1
1Graduate School of Engineering, The University of Tokyo, Tokyo, Japan.
Background:
Visualization of the vast placental vasculature is crucial in fetoscopic laser photocoagulation for twin-to-twin transfusion syndrome treatment. However, vasculature mosaic is challenging due to the fluctuating imaging conditions during fetoscopic surgery.
Method:
A scene adaptive feature-based approach for image correspondence in free-hand endoscopic placental video is proposed. It contributes towards existing techniques by introducing a failure detection method based on statistical attributes of the feature distribution, and an updating mechanism that self-tunes parameters to recover from registration failures.
Results:
Validations on endoscopic image sequences of a phantom and a monkey placenta are carried out to demonstrate mismatch recovery. In two 100-frame sequences, automatic self-tuned results improved by 8% compared with manual experience-based tuning and a slight 2.5% deterioration against exhaustive tuning (gold standard).
Conclusion:
This scene-adaptive image correspondence approach, which is not restricted to a set of generalized parameters, is suitable for applications associated with dynamically changing imaging conditions. Copyright © 2015 John Wiley & Sons, Ltd.
