一种新的视网膜共聚焦内镜扫描半自主控制框架。

Zhaoshuo Li, Mahya Shahbazi, Niravkumar Patel, Eimear O' Sullivan, Haojie Zhang, Khushi Vyas, Preetham Chalasani, Peter L Gehlbach, Iulian Iordachita, Guang-Zhong Yang, Russell H Taylor
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引用次数: 3

摘要

本文提出了一种新的半自主控制框架,用于实现基于探针的共聚焦激光内镜(pCLE)对视网膜组织的扫描。使用pCLE,可以实时扫描和表征视网膜各层,如神经纤维层(NFL)和视网膜神经节细胞(RGC),以提高诊断和手术结果预测。然而,pCLE系统的有限视野和探针的微米级最佳聚焦距离,在生理手部震颤的顺序上,成为成功手动扫描视网膜组织的障碍。因此,提出了一种新的无传感器框架,用于视网膜手术期间的实时半自主内镜扫描。该框架由与pCLE系统集成的稳定手眼机器人(SHER)组成,其中探头的运动是半自主控制的。通过混合运动控制策略,该系统自动控制共聚焦探头,以优化pCLE图像的清晰度和质量,同时为外科医生提供无震颤扫描组织的能力。通过实验评估和涉及9名参与者的用户研究,验证了所提出架构的有效性。通过统计分析表明,该框架可以显著减少用户的工作量,同时也提高了用户保留最佳质量的pCLE图像的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Semi-Autonomous Control Framework for Retina Confocal Endomicroscopy Scanning.

In this paper, a novel semi-autonomous control framework is presented for enabling probe-based confocal laser endomicroscopy (pCLE) scan of the retinal tissue. With pCLE, retinal layers such as nerve fiber layer (NFL) and retinal ganglion cell (RGC) can be scanned and characterized in real-time for an improved diagnosis and surgical outcome prediction. However, the limited field of view of the pCLE system and the micron-scale optimal focus distance of the probe, which are in the order of physiological hand tremor, act as barriers to successful manual scan of retinal tissue. Therefore, a novel sensorless framework is proposed for real-time semi-autonomous endomicroscopy scanning during retinal surgery. The framework consists of the Steady-Hand Eye Robot (SHER) integrated with a pCLE system, where the motion of the probe is controlled semi-autonomously. Through a hybrid motion control strategy, the system autonomously controls the confocal probe to optimize the sharpness and quality of the pCLE images, while providing the surgeon with the ability to scan the tissue in a tremor-free manner. Effectiveness of the proposed architecture is validated through experimental evaluations as well as a user study involving 9 participants. It is shown through statistical analyses that the proposed framework can reduce the work load experienced by the users in a statistically-significant manner, while also enhancing their performance in retaining pCLE images with optimized quality.

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