A Framework for Sensorless Tissue Motion Tracking in Robotic Endomicroscopy Scanning

摘要

Recent advances in probe-based Confocal Laser Endomicroscopy (pCLE) enable real-time, in situ and in vivo tissue assessment at the micro scale. The limited field-of-view offered by pCLE necessitates the use of mosaicking to allow for accurate tissue characterization from the incoming image stream. However, mosaicking requires a series of contiguous good-quality images, which is particularly challenging because probe-tissue distance must be maintained within a very narrow working range at all times and probe-tissue contact force must be kept to a minimum so that tissue deformation is avoided. Robotic manipulation of the endomicroscopy probe has provided partial solution to these challenges, but sensorless approaches have not been thoroughly investigated up to date. This paper proposes a novel sensorless framework that uses a single non-reference image-quality metric to learn an approximation of tissue motion and subsequently track it. Moreover, a pCLE robotic tool for autonomous endomicroscopy scanning is designed and used for testing and validation purposes. Experiments on lens paper and ex vivo porcine tissue validate the philosophy of the framework.