Fast 5DOF needle tracking in iOCT

Purpose Intraoperative optical coherence tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the...
Ausführliche Beschreibung

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Autor*in:	Weiss, Jakob [verfasserIn] Rieke, Nicola Nasseri, Mohammad Ali Maier, Mathias Eslami, Abouzar Navab, Nassir

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Optical coherence tomography iOCT Instrument tracking Ophthalmic tool tracking Geometric modeling

Anmerkung:	© CARS 2018

Übergeordnetes Werk:	Enthalten in: International journal of computer assisted radiology and surgery - Berlin : Springer, 2006, 13(2018), 6 vom: 30. März, Seite 787-796
Übergeordnetes Werk:	volume:13 ; year:2018 ; number:6 ; day:30 ; month:03 ; pages:787-796

Links:	Volltext

DOI / URN:	10.1007/s11548-018-1751-5

Katalog-ID:	SPR020712979

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520			\|a Purpose Intraoperative optical coherence tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle. Thereby, we enable the direct analysis of instrument–tissue interaction directly in OCT space without complex multimodal calibration that would be required with traditional instrument tracking methods. Method The intersection of the needle with the iOCT scan is detected by a peculiar multistep ellipse fitting that takes advantage of the directionality of the modality. The geometric modeling allows us to use the ellipse parameters and provide them into a latency-aware estimator to infer the 5DOF pose during needle movement. Results Experiments on phantom data and ex vivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods. Conclusion Using solely cross-sectional iOCT information, we are able to successfully and robustly estimate a 5DOF pose of the instrument in less than 5.4 ms on a CPU.
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650		4	\|a iOCT \|7 (dpeaa)DE-He213
650		4	\|a Instrument tracking \|7 (dpeaa)DE-He213
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700	1		\|a Navab, Nassir \|4 aut
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allfields	10.1007/s11548-018-1751-5 doi (DE-627)SPR020712979 (SPR)s11548-018-1751-5-e DE-627 ger DE-627 rakwb eng Weiss, Jakob verfasserin (orcid)0000-0002-4058-2485 aut Fast 5DOF needle tracking in iOCT 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © CARS 2018 Purpose Intraoperative optical coherence tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle. Thereby, we enable the direct analysis of instrument–tissue interaction directly in OCT space without complex multimodal calibration that would be required with traditional instrument tracking methods. Method The intersection of the needle with the iOCT scan is detected by a peculiar multistep ellipse fitting that takes advantage of the directionality of the modality. The geometric modeling allows us to use the ellipse parameters and provide them into a latency-aware estimator to infer the 5DOF pose during needle movement. Results Experiments on phantom data and ex vivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods. Conclusion Using solely cross-sectional iOCT information, we are able to successfully and robustly estimate a 5DOF pose of the instrument in less than 5.4 ms on a CPU. Optical coherence tomography (dpeaa)DE-He213 iOCT (dpeaa)DE-He213 Instrument tracking (dpeaa)DE-He213 Ophthalmic tool tracking (dpeaa)DE-He213 Geometric modeling (dpeaa)DE-He213 Rieke, Nicola aut Nasseri, Mohammad Ali aut Maier, Mathias aut Eslami, Abouzar aut Navab, Nassir aut Enthalten in International journal of computer assisted radiology and surgery Berlin : Springer, 2006 13(2018), 6 vom: 30. März, Seite 787-796 (DE-627)512299250 (DE-600)2235881-X 1861-6429 nnns volume:13 year:2018 number:6 day:30 month:03 pages:787-796 https://dx.doi.org/10.1007/s11548-018-1751-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2018 6 30 03 787-796
spelling	10.1007/s11548-018-1751-5 doi (DE-627)SPR020712979 (SPR)s11548-018-1751-5-e DE-627 ger DE-627 rakwb eng Weiss, Jakob verfasserin (orcid)0000-0002-4058-2485 aut Fast 5DOF needle tracking in iOCT 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © CARS 2018 Purpose Intraoperative optical coherence tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle. Thereby, we enable the direct analysis of instrument–tissue interaction directly in OCT space without complex multimodal calibration that would be required with traditional instrument tracking methods. Method The intersection of the needle with the iOCT scan is detected by a peculiar multistep ellipse fitting that takes advantage of the directionality of the modality. The geometric modeling allows us to use the ellipse parameters and provide them into a latency-aware estimator to infer the 5DOF pose during needle movement. Results Experiments on phantom data and ex vivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods. Conclusion Using solely cross-sectional iOCT information, we are able to successfully and robustly estimate a 5DOF pose of the instrument in less than 5.4 ms on a CPU. Optical coherence tomography (dpeaa)DE-He213 iOCT (dpeaa)DE-He213 Instrument tracking (dpeaa)DE-He213 Ophthalmic tool tracking (dpeaa)DE-He213 Geometric modeling (dpeaa)DE-He213 Rieke, Nicola aut Nasseri, Mohammad Ali aut Maier, Mathias aut Eslami, Abouzar aut Navab, Nassir aut Enthalten in International journal of computer assisted radiology and surgery Berlin : Springer, 2006 13(2018), 6 vom: 30. März, Seite 787-796 (DE-627)512299250 (DE-600)2235881-X 1861-6429 nnns volume:13 year:2018 number:6 day:30 month:03 pages:787-796 https://dx.doi.org/10.1007/s11548-018-1751-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2018 6 30 03 787-796
allfields_unstemmed	10.1007/s11548-018-1751-5 doi (DE-627)SPR020712979 (SPR)s11548-018-1751-5-e DE-627 ger DE-627 rakwb eng Weiss, Jakob verfasserin (orcid)0000-0002-4058-2485 aut Fast 5DOF needle tracking in iOCT 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © CARS 2018 Purpose Intraoperative optical coherence tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle. Thereby, we enable the direct analysis of instrument–tissue interaction directly in OCT space without complex multimodal calibration that would be required with traditional instrument tracking methods. Method The intersection of the needle with the iOCT scan is detected by a peculiar multistep ellipse fitting that takes advantage of the directionality of the modality. The geometric modeling allows us to use the ellipse parameters and provide them into a latency-aware estimator to infer the 5DOF pose during needle movement. Results Experiments on phantom data and ex vivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods. Conclusion Using solely cross-sectional iOCT information, we are able to successfully and robustly estimate a 5DOF pose of the instrument in less than 5.4 ms on a CPU. Optical coherence tomography (dpeaa)DE-He213 iOCT (dpeaa)DE-He213 Instrument tracking (dpeaa)DE-He213 Ophthalmic tool tracking (dpeaa)DE-He213 Geometric modeling (dpeaa)DE-He213 Rieke, Nicola aut Nasseri, Mohammad Ali aut Maier, Mathias aut Eslami, Abouzar aut Navab, Nassir aut Enthalten in International journal of computer assisted radiology and surgery Berlin : Springer, 2006 13(2018), 6 vom: 30. März, Seite 787-796 (DE-627)512299250 (DE-600)2235881-X 1861-6429 nnns volume:13 year:2018 number:6 day:30 month:03 pages:787-796 https://dx.doi.org/10.1007/s11548-018-1751-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2018 6 30 03 787-796
allfieldsGer	10.1007/s11548-018-1751-5 doi (DE-627)SPR020712979 (SPR)s11548-018-1751-5-e DE-627 ger DE-627 rakwb eng Weiss, Jakob verfasserin (orcid)0000-0002-4058-2485 aut Fast 5DOF needle tracking in iOCT 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © CARS 2018 Purpose Intraoperative optical coherence tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle. Thereby, we enable the direct analysis of instrument–tissue interaction directly in OCT space without complex multimodal calibration that would be required with traditional instrument tracking methods. Method The intersection of the needle with the iOCT scan is detected by a peculiar multistep ellipse fitting that takes advantage of the directionality of the modality. The geometric modeling allows us to use the ellipse parameters and provide them into a latency-aware estimator to infer the 5DOF pose during needle movement. Results Experiments on phantom data and ex vivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods. Conclusion Using solely cross-sectional iOCT information, we are able to successfully and robustly estimate a 5DOF pose of the instrument in less than 5.4 ms on a CPU. Optical coherence tomography (dpeaa)DE-He213 iOCT (dpeaa)DE-He213 Instrument tracking (dpeaa)DE-He213 Ophthalmic tool tracking (dpeaa)DE-He213 Geometric modeling (dpeaa)DE-He213 Rieke, Nicola aut Nasseri, Mohammad Ali aut Maier, Mathias aut Eslami, Abouzar aut Navab, Nassir aut Enthalten in International journal of computer assisted radiology and surgery Berlin : Springer, 2006 13(2018), 6 vom: 30. März, Seite 787-796 (DE-627)512299250 (DE-600)2235881-X 1861-6429 nnns volume:13 year:2018 number:6 day:30 month:03 pages:787-796 https://dx.doi.org/10.1007/s11548-018-1751-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2018 6 30 03 787-796
allfieldsSound	10.1007/s11548-018-1751-5 doi (DE-627)SPR020712979 (SPR)s11548-018-1751-5-e DE-627 ger DE-627 rakwb eng Weiss, Jakob verfasserin (orcid)0000-0002-4058-2485 aut Fast 5DOF needle tracking in iOCT 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © CARS 2018 Purpose Intraoperative optical coherence tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle. Thereby, we enable the direct analysis of instrument–tissue interaction directly in OCT space without complex multimodal calibration that would be required with traditional instrument tracking methods. Method The intersection of the needle with the iOCT scan is detected by a peculiar multistep ellipse fitting that takes advantage of the directionality of the modality. The geometric modeling allows us to use the ellipse parameters and provide them into a latency-aware estimator to infer the 5DOF pose during needle movement. Results Experiments on phantom data and ex vivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods. Conclusion Using solely cross-sectional iOCT information, we are able to successfully and robustly estimate a 5DOF pose of the instrument in less than 5.4 ms on a CPU. Optical coherence tomography (dpeaa)DE-He213 iOCT (dpeaa)DE-He213 Instrument tracking (dpeaa)DE-He213 Ophthalmic tool tracking (dpeaa)DE-He213 Geometric modeling (dpeaa)DE-He213 Rieke, Nicola aut Nasseri, Mohammad Ali aut Maier, Mathias aut Eslami, Abouzar aut Navab, Nassir aut Enthalten in International journal of computer assisted radiology and surgery Berlin : Springer, 2006 13(2018), 6 vom: 30. März, Seite 787-796 (DE-627)512299250 (DE-600)2235881-X 1861-6429 nnns volume:13 year:2018 number:6 day:30 month:03 pages:787-796 https://dx.doi.org/10.1007/s11548-018-1751-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2018 6 30 03 787-796
language	English
source	Enthalten in International journal of computer assisted radiology and surgery 13(2018), 6 vom: 30. März, Seite 787-796 volume:13 year:2018 number:6 day:30 month:03 pages:787-796
sourceStr	Enthalten in International journal of computer assisted radiology and surgery 13(2018), 6 vom: 30. März, Seite 787-796 volume:13 year:2018 number:6 day:30 month:03 pages:787-796
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Optical coherence tomography iOCT Instrument tracking Ophthalmic tool tracking Geometric modeling
isfreeaccess_bool	false
container_title	International journal of computer assisted radiology and surgery
authorswithroles_txt_mv	Weiss, Jakob @@aut@@ Rieke, Nicola @@aut@@ Nasseri, Mohammad Ali @@aut@@ Maier, Mathias @@aut@@ Eslami, Abouzar @@aut@@ Navab, Nassir @@aut@@
publishDateDaySort_date	2018-03-30T00:00:00Z
hierarchy_top_id	512299250
id	SPR020712979
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR020712979</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230520012651.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201006s2018 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11548-018-1751-5</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR020712979</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11548-018-1751-5-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Weiss, Jakob</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-4058-2485</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Fast 5DOF needle tracking in iOCT</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© CARS 2018</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Purpose Intraoperative optical coherence tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle. Thereby, we enable the direct analysis of instrument–tissue interaction directly in OCT space without complex multimodal calibration that would be required with traditional instrument tracking methods. Method The intersection of the needle with the iOCT scan is detected by a peculiar multistep ellipse fitting that takes advantage of the directionality of the modality. The geometric modeling allows us to use the ellipse parameters and provide them into a latency-aware estimator to infer the 5DOF pose during needle movement. Results Experiments on phantom data and ex vivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods. 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März, Seite 787-796</subfield><subfield code="w">(DE-627)512299250</subfield><subfield code="w">(DE-600)2235881-X</subfield><subfield code="x">1861-6429</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:13</subfield><subfield code="g">year:2018</subfield><subfield code="g">number:6</subfield><subfield code="g">day:30</subfield><subfield code="g">month:03</subfield><subfield code="g">pages:787-796</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s11548-018-1751-5</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" 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author	Weiss, Jakob
spellingShingle	Weiss, Jakob misc Optical coherence tomography misc iOCT misc Instrument tracking misc Ophthalmic tool tracking misc Geometric modeling Fast 5DOF needle tracking in iOCT
authorStr	Weiss, Jakob
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topic_title	Fast 5DOF needle tracking in iOCT Optical coherence tomography (dpeaa)DE-He213 iOCT (dpeaa)DE-He213 Instrument tracking (dpeaa)DE-He213 Ophthalmic tool tracking (dpeaa)DE-He213 Geometric modeling (dpeaa)DE-He213
topic	misc Optical coherence tomography misc iOCT misc Instrument tracking misc Ophthalmic tool tracking misc Geometric modeling
topic_unstemmed	misc Optical coherence tomography misc iOCT misc Instrument tracking misc Ophthalmic tool tracking misc Geometric modeling
topic_browse	misc Optical coherence tomography misc iOCT misc Instrument tracking misc Ophthalmic tool tracking misc Geometric modeling
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title	Fast 5DOF needle tracking in iOCT
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title_full	Fast 5DOF needle tracking in iOCT
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journal	International journal of computer assisted radiology and surgery
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author_browse	Weiss, Jakob Rieke, Nicola Nasseri, Mohammad Ali Maier, Mathias Eslami, Abouzar Navab, Nassir
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author-letter	Weiss, Jakob
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title_sort	fast 5dof needle tracking in ioct
title_auth	Fast 5DOF needle tracking in iOCT
abstract	Purpose Intraoperative optical coherence tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle. Thereby, we enable the direct analysis of instrument–tissue interaction directly in OCT space without complex multimodal calibration that would be required with traditional instrument tracking methods. Method The intersection of the needle with the iOCT scan is detected by a peculiar multistep ellipse fitting that takes advantage of the directionality of the modality. The geometric modeling allows us to use the ellipse parameters and provide them into a latency-aware estimator to infer the 5DOF pose during needle movement. Results Experiments on phantom data and ex vivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods. Conclusion Using solely cross-sectional iOCT information, we are able to successfully and robustly estimate a 5DOF pose of the instrument in less than 5.4 ms on a CPU. © CARS 2018
abstractGer	Purpose Intraoperative optical coherence tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle. Thereby, we enable the direct analysis of instrument–tissue interaction directly in OCT space without complex multimodal calibration that would be required with traditional instrument tracking methods. Method The intersection of the needle with the iOCT scan is detected by a peculiar multistep ellipse fitting that takes advantage of the directionality of the modality. The geometric modeling allows us to use the ellipse parameters and provide them into a latency-aware estimator to infer the 5DOF pose during needle movement. Results Experiments on phantom data and ex vivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods. Conclusion Using solely cross-sectional iOCT information, we are able to successfully and robustly estimate a 5DOF pose of the instrument in less than 5.4 ms on a CPU. © CARS 2018
abstract_unstemmed	Purpose Intraoperative optical coherence tomography (iOCT) is an increasingly available imaging technique for ophthalmic microsurgery that provides high-resolution cross-sectional information of the surgical scene. We propose to build on its desirable qualities and present a method for tracking the orientation and location of a surgical needle. Thereby, we enable the direct analysis of instrument–tissue interaction directly in OCT space without complex multimodal calibration that would be required with traditional instrument tracking methods. Method The intersection of the needle with the iOCT scan is detected by a peculiar multistep ellipse fitting that takes advantage of the directionality of the modality. The geometric modeling allows us to use the ellipse parameters and provide them into a latency-aware estimator to infer the 5DOF pose during needle movement. Results Experiments on phantom data and ex vivo porcine eyes indicate that the algorithm retains angular precision especially during lateral needle movement and provides a more robust and consistent estimation than baseline methods. Conclusion Using solely cross-sectional iOCT information, we are able to successfully and robustly estimate a 5DOF pose of the instrument in less than 5.4 ms on a CPU. © CARS 2018
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container_issue	6
title_short	Fast 5DOF needle tracking in iOCT
url	https://dx.doi.org/10.1007/s11548-018-1751-5
remote_bool	true
author2	Rieke, Nicola Nasseri, Mohammad Ali Maier, Mathias Eslami, Abouzar Navab, Nassir
author2Str	Rieke, Nicola Nasseri, Mohammad Ali Maier, Mathias Eslami, Abouzar Navab, Nassir
ppnlink	512299250
mediatype_str_mv	c
isOA_txt	false
hochschulschrift_bool	false
doi_str	10.1007/s11548-018-1751-5
up_date	2024-07-03T17:47:08.040Z
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