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...
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| Vydané v: | Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems Ročník 2019; s. 7083 - 7090 |
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| Hlavní autori: | , , , , , , , , , , |
| Médium: | Konferenčný príspevok.. Journal Article |
| Jazyk: | English |
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United States
IEEE
01.11.2019
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| ISSN: | 2153-0858, 2153-0866 |
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| Abstract | 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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| AbstractList | 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. 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.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. |
| Author | Shahbazi, Mahya Patel, Niravkumar Taylor, Russell H. Sullivan, Eimear O Vyas, Khushi Gehlbach, Peter L. Yang, Guang-Zhong Iordachita, Iulian Li, Zhaoshuo Zhang, Haojie Chalasani, Preetham |
| AuthorAffiliation | 1 Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, Maryland 21218, USA 2 Hamlyn Centre for Robotic Surgery, Imperial College London, SW7 2AZ, London, UK 3 Johns Hopkins Wilmer Eye Institute, Johns Hopkins Hospital, 600 N. Wolfe Street, Maryland 21287, USA |
| AuthorAffiliation_xml | – name: 2 Hamlyn Centre for Robotic Surgery, Imperial College London, SW7 2AZ, London, UK – name: 3 Johns Hopkins Wilmer Eye Institute, Johns Hopkins Hospital, 600 N. Wolfe Street, Maryland 21287, USA – name: 1 Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, Maryland 21218, USA |
| Author_xml | – sequence: 1 givenname: Zhaoshuo surname: Li fullname: Li, Zhaoshuo organization: Johns Hopkins University,Laboratory for Computational Sensing and Robotics,Maryland,Baltimore,USA,21218 – sequence: 2 givenname: Mahya surname: Shahbazi fullname: Shahbazi, Mahya organization: Johns Hopkins University,Laboratory for Computational Sensing and Robotics,Maryland,Baltimore,USA,21218 – sequence: 3 givenname: Niravkumar surname: Patel fullname: Patel, Niravkumar organization: Johns Hopkins University,Laboratory for Computational Sensing and Robotics,Maryland,Baltimore,USA,21218 – sequence: 4 givenname: Eimear O' surname: Sullivan fullname: Sullivan, Eimear O' organization: Hamlyn Centre for Robotic Surgery, Imperial College London,London,UK,SW7 2AZ – sequence: 5 givenname: Haojie surname: Zhang fullname: Zhang, Haojie organization: Hamlyn Centre for Robotic Surgery, Imperial College London,London,UK,SW7 2AZ – sequence: 6 givenname: Khushi surname: Vyas fullname: Vyas, Khushi organization: Hamlyn Centre for Robotic Surgery, Imperial College London,London,UK,SW7 2AZ – sequence: 7 givenname: Preetham surname: Chalasani fullname: Chalasani, Preetham organization: Johns Hopkins University,Laboratory for Computational Sensing and Robotics,Maryland,Baltimore,USA,21218 – sequence: 8 givenname: Peter L. surname: Gehlbach fullname: Gehlbach, Peter L. organization: Johns Hopkins Wilmer Eye Institute,Johns Hopkins Hospital,600 N. Wolfe Street, Maryland,USA,21287 – sequence: 9 givenname: Iulian surname: Iordachita fullname: Iordachita, Iulian organization: Johns Hopkins University,Laboratory for Computational Sensing and Robotics,Maryland,Baltimore,USA,21218 – sequence: 10 givenname: Guang-Zhong surname: Yang fullname: Yang, Guang-Zhong organization: Hamlyn Centre for Robotic Surgery, Imperial College London,London,UK,SW7 2AZ – sequence: 11 givenname: Russell H. surname: Taylor fullname: Taylor, Russell H. organization: Johns Hopkins University,Laboratory for Computational Sensing and Robotics,Maryland,Baltimore,USA,21218 |
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| SubjectTerms | Computer architecture Endomicroscopy Probes Real-time systems Retina Robot sensing systems Surgery |
| Title | A Novel Semi-Autonomous Control Framework for Retina Confocal Endomicroscopy Scanning |
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