6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery

Vitreoretinal (VR) surgery is typical microsurgery with delicate and complex surgical procedures. The vision-based navigation for robot-assisted VR surgery has not been fully exploited because of the challenges that arise from illumination, high precision, and safety assessments. This paper presents...
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Autor*in:	Mingchuan Zhou [verfasserIn] Xing Hao [verfasserIn] Abouzar Eslami [verfasserIn] Kai Huang [verfasserIn] Caixia Cai [verfasserIn] Chris P. Lohmann [verfasserIn] Nassir Navab [verfasserIn] Alois Knoll [verfasserIn] M. Ali Nasseri [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Biomedical engineering biomedical image processing biomedical signal processing medical robotics

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 7(2019), Seite 63113-63122
Übergeordnetes Werk:	volume:7 ; year:2019 ; pages:63113-63122

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2019.2912327

Katalog-ID:	DOAJ007592949

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spelling	10.1109/ACCESS.2019.2912327 doi (DE-627)DOAJ007592949 (DE-599)DOAJ31a73c366e2f43e9a51bc77611db6d9a DE-627 ger DE-627 rakwb eng TK1-9971 Mingchuan Zhou verfasserin aut 6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Vitreoretinal (VR) surgery is typical microsurgery with delicate and complex surgical procedures. The vision-based navigation for robot-assisted VR surgery has not been fully exploited because of the challenges that arise from illumination, high precision, and safety assessments. This paper presents a novel method to estimate the 6DOF needle pose specifically for the application of robotic intraocular needle navigation using optical coherence tomography (OCT) volumes. The key ingredients of the proposed method are (1) 3D needle point cloud segmentation in OCT volume and (2) needle point cloud 6DOF pose estimation using a modified iterative closest point (ICP) algorithm. To address the former, a voting mechanism with geometric features of the needle is utilized to robustly segment the needle in OCT volume. Afterward, the CAD model of the needle point cloud is matched with the segmented needle point cloud to estimate the 6DOF needle pose with a proposed shift-rotate ICP (SR-ICP). This method is evaluated by the existing ophthalmic robot on ex-vivo pig eyes. The quantitative and qualitative results are evaluated and presented for the proposed method. Biomedical engineering biomedical image processing biomedical signal processing medical robotics Electrical engineering. Electronics. Nuclear engineering Xing Hao verfasserin aut Abouzar Eslami verfasserin aut Kai Huang verfasserin aut Caixia Cai verfasserin aut Chris P. Lohmann verfasserin aut Nassir Navab verfasserin aut Alois Knoll verfasserin aut M. Ali Nasseri verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 63113-63122 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:63113-63122 https://doi.org/10.1109/ACCESS.2019.2912327 kostenfrei https://doaj.org/article/31a73c366e2f43e9a51bc77611db6d9a kostenfrei https://ieeexplore.ieee.org/document/8695065/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 63113-63122
allfields_unstemmed	10.1109/ACCESS.2019.2912327 doi (DE-627)DOAJ007592949 (DE-599)DOAJ31a73c366e2f43e9a51bc77611db6d9a DE-627 ger DE-627 rakwb eng TK1-9971 Mingchuan Zhou verfasserin aut 6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Vitreoretinal (VR) surgery is typical microsurgery with delicate and complex surgical procedures. The vision-based navigation for robot-assisted VR surgery has not been fully exploited because of the challenges that arise from illumination, high precision, and safety assessments. This paper presents a novel method to estimate the 6DOF needle pose specifically for the application of robotic intraocular needle navigation using optical coherence tomography (OCT) volumes. The key ingredients of the proposed method are (1) 3D needle point cloud segmentation in OCT volume and (2) needle point cloud 6DOF pose estimation using a modified iterative closest point (ICP) algorithm. To address the former, a voting mechanism with geometric features of the needle is utilized to robustly segment the needle in OCT volume. Afterward, the CAD model of the needle point cloud is matched with the segmented needle point cloud to estimate the 6DOF needle pose with a proposed shift-rotate ICP (SR-ICP). This method is evaluated by the existing ophthalmic robot on ex-vivo pig eyes. The quantitative and qualitative results are evaluated and presented for the proposed method. Biomedical engineering biomedical image processing biomedical signal processing medical robotics Electrical engineering. Electronics. Nuclear engineering Xing Hao verfasserin aut Abouzar Eslami verfasserin aut Kai Huang verfasserin aut Caixia Cai verfasserin aut Chris P. Lohmann verfasserin aut Nassir Navab verfasserin aut Alois Knoll verfasserin aut M. Ali Nasseri verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 63113-63122 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:63113-63122 https://doi.org/10.1109/ACCESS.2019.2912327 kostenfrei https://doaj.org/article/31a73c366e2f43e9a51bc77611db6d9a kostenfrei https://ieeexplore.ieee.org/document/8695065/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 63113-63122
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callnumber-first	T - Technology
author	Mingchuan Zhou
spellingShingle	Mingchuan Zhou misc TK1-9971 misc Biomedical engineering misc biomedical image processing misc biomedical signal processing misc medical robotics misc Electrical engineering. Electronics. Nuclear engineering 6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery
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topic_title	TK1-9971 6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery Biomedical engineering biomedical image processing biomedical signal processing medical robotics
topic	misc TK1-9971 misc Biomedical engineering misc biomedical image processing misc biomedical signal processing misc medical robotics misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Biomedical engineering misc biomedical image processing misc biomedical signal processing misc medical robotics misc Electrical engineering. Electronics. Nuclear engineering
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title	6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery
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title_full	6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery
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title_sort	6dof needle pose estimation for robot-assisted vitreoretinal surgery
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title_auth	6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery
abstract	Vitreoretinal (VR) surgery is typical microsurgery with delicate and complex surgical procedures. The vision-based navigation for robot-assisted VR surgery has not been fully exploited because of the challenges that arise from illumination, high precision, and safety assessments. This paper presents a novel method to estimate the 6DOF needle pose specifically for the application of robotic intraocular needle navigation using optical coherence tomography (OCT) volumes. The key ingredients of the proposed method are (1) 3D needle point cloud segmentation in OCT volume and (2) needle point cloud 6DOF pose estimation using a modified iterative closest point (ICP) algorithm. To address the former, a voting mechanism with geometric features of the needle is utilized to robustly segment the needle in OCT volume. Afterward, the CAD model of the needle point cloud is matched with the segmented needle point cloud to estimate the 6DOF needle pose with a proposed shift-rotate ICP (SR-ICP). This method is evaluated by the existing ophthalmic robot on ex-vivo pig eyes. The quantitative and qualitative results are evaluated and presented for the proposed method.
abstractGer	Vitreoretinal (VR) surgery is typical microsurgery with delicate and complex surgical procedures. The vision-based navigation for robot-assisted VR surgery has not been fully exploited because of the challenges that arise from illumination, high precision, and safety assessments. This paper presents a novel method to estimate the 6DOF needle pose specifically for the application of robotic intraocular needle navigation using optical coherence tomography (OCT) volumes. The key ingredients of the proposed method are (1) 3D needle point cloud segmentation in OCT volume and (2) needle point cloud 6DOF pose estimation using a modified iterative closest point (ICP) algorithm. To address the former, a voting mechanism with geometric features of the needle is utilized to robustly segment the needle in OCT volume. Afterward, the CAD model of the needle point cloud is matched with the segmented needle point cloud to estimate the 6DOF needle pose with a proposed shift-rotate ICP (SR-ICP). This method is evaluated by the existing ophthalmic robot on ex-vivo pig eyes. The quantitative and qualitative results are evaluated and presented for the proposed method.
abstract_unstemmed	Vitreoretinal (VR) surgery is typical microsurgery with delicate and complex surgical procedures. The vision-based navigation for robot-assisted VR surgery has not been fully exploited because of the challenges that arise from illumination, high precision, and safety assessments. This paper presents a novel method to estimate the 6DOF needle pose specifically for the application of robotic intraocular needle navigation using optical coherence tomography (OCT) volumes. The key ingredients of the proposed method are (1) 3D needle point cloud segmentation in OCT volume and (2) needle point cloud 6DOF pose estimation using a modified iterative closest point (ICP) algorithm. To address the former, a voting mechanism with geometric features of the needle is utilized to robustly segment the needle in OCT volume. Afterward, the CAD model of the needle point cloud is matched with the segmented needle point cloud to estimate the 6DOF needle pose with a proposed shift-rotate ICP (SR-ICP). This method is evaluated by the existing ophthalmic robot on ex-vivo pig eyes. The quantitative and qualitative results are evaluated and presented for the proposed method.
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title_short	6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery
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