TY - GEN
T1 - A Novel Semi-Autonomous Control Framework for Retina Confocal Endomicroscopy Scanning
AU - Li, Zhaoshuo
AU - Yang, Guang Zhong
AU - Taylor, Russell H.
AU - Shahbazi, Mahya
AU - Patel, Niravkumar
AU - Sullivan, Eimear O.
AU - Zhang, Haojie
AU - Vyas, Khushi
AU - Chalasani, Preetham
AU - Gehlbach, Peter L.
AU - Iordachita, Iulian
N1 - Funding Information:
* This work was funded in part by: NSF NRI Grants IIS-1327657, 1637789; Natural Sciences and Engineering Research Council of Canada (NSERC) Postdoctoral Fellowship #516873; Johns Hopkins internal funds; Robotic Endobronchial Optical Tomography (REBOT) Grant EP/N019318/1; EP/P012779/1 Micro-robotics for Surgery; and NIH R01 Grant 1R01EB023943-01.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - 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.
AB - 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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U2 - 10.1109/IROS40897.2019.8967751
DO - 10.1109/IROS40897.2019.8967751
M3 - Conference contribution
AN - SCOPUS:85081156849
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 7083
EP - 7090
BT - 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
Y2 - 3 November 2019 through 8 November 2019
ER -