Medical image registration based on SURF detector

Abstract A quick method of 2D global registration of CT images in different series of studies of one patient is suggested in this work. The distinguishing feature of this approach is the use of image registration based on the SURF (Speeded Up Robust Features) detector, which has proved efficient in...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Lukashevich, P. V. [verfasserIn] Zalesky, B. A. Ablameyko, S. V.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2011

Schlagwörter:	Image Registration Robust Feature DICOM Image Perspective Transformation Medical Image Registration

Anmerkung:	© Pleiades Publishing, Ltd. 2011

Übergeordnetes Werk:	Enthalten in: Pattern recognition and image analysis - Moscow : MAIK Nauka/Interperiodica Publ., 1996, 21(2011), 3 vom: 13. Sept.
Übergeordnetes Werk:	volume:21 ; year:2011 ; number:3 ; day:13 ; month:09

Links:	Volltext

DOI / URN:	10.1134/S1054661811020696

Katalog-ID:	SPR020176368

Internformat


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520			\|a Abstract A quick method of 2D global registration of CT images in different series of studies of one patient is suggested in this work. The distinguishing feature of this approach is the use of image registration based on the SURF (Speeded Up Robust Features) detector, which has proved efficient in computer vision.
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650		4	\|a Robust Feature \|7 (dpeaa)DE-He213
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650		4	\|a Perspective Transformation \|7 (dpeaa)DE-He213
650		4	\|a Medical Image Registration \|7 (dpeaa)DE-He213
700	1		\|a Zalesky, B. A. \|4 aut
700	1		\|a Ablameyko, S. V. \|4 aut
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912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_2548
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allfields	10.1134/S1054661811020696 doi (DE-627)SPR020176368 (SPR)S1054661811020696-e DE-627 ger DE-627 rakwb eng Lukashevich, P. V. verfasserin aut Medical image registration based on SURF detector 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2011 Abstract A quick method of 2D global registration of CT images in different series of studies of one patient is suggested in this work. The distinguishing feature of this approach is the use of image registration based on the SURF (Speeded Up Robust Features) detector, which has proved efficient in computer vision. Image Registration (dpeaa)DE-He213 Robust Feature (dpeaa)DE-He213 DICOM Image (dpeaa)DE-He213 Perspective Transformation (dpeaa)DE-He213 Medical Image Registration (dpeaa)DE-He213 Zalesky, B. A. aut Ablameyko, S. V. aut Enthalten in Pattern recognition and image analysis Moscow : MAIK Nauka/Interperiodica Publ., 1996 21(2011), 3 vom: 13. Sept. (DE-627)327148179 (DE-600)2044032-7 1555-6212 nnns volume:21 year:2011 number:3 day:13 month:09 https://dx.doi.org/10.1134/S1054661811020696 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 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_4126 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 21 2011 3 13 09
spelling	10.1134/S1054661811020696 doi (DE-627)SPR020176368 (SPR)S1054661811020696-e DE-627 ger DE-627 rakwb eng Lukashevich, P. V. verfasserin aut Medical image registration based on SURF detector 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2011 Abstract A quick method of 2D global registration of CT images in different series of studies of one patient is suggested in this work. The distinguishing feature of this approach is the use of image registration based on the SURF (Speeded Up Robust Features) detector, which has proved efficient in computer vision. Image Registration (dpeaa)DE-He213 Robust Feature (dpeaa)DE-He213 DICOM Image (dpeaa)DE-He213 Perspective Transformation (dpeaa)DE-He213 Medical Image Registration (dpeaa)DE-He213 Zalesky, B. A. aut Ablameyko, S. V. aut Enthalten in Pattern recognition and image analysis Moscow : MAIK Nauka/Interperiodica Publ., 1996 21(2011), 3 vom: 13. Sept. (DE-627)327148179 (DE-600)2044032-7 1555-6212 nnns volume:21 year:2011 number:3 day:13 month:09 https://dx.doi.org/10.1134/S1054661811020696 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 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_4126 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 21 2011 3 13 09
allfields_unstemmed	10.1134/S1054661811020696 doi (DE-627)SPR020176368 (SPR)S1054661811020696-e DE-627 ger DE-627 rakwb eng Lukashevich, P. V. verfasserin aut Medical image registration based on SURF detector 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2011 Abstract A quick method of 2D global registration of CT images in different series of studies of one patient is suggested in this work. The distinguishing feature of this approach is the use of image registration based on the SURF (Speeded Up Robust Features) detector, which has proved efficient in computer vision. Image Registration (dpeaa)DE-He213 Robust Feature (dpeaa)DE-He213 DICOM Image (dpeaa)DE-He213 Perspective Transformation (dpeaa)DE-He213 Medical Image Registration (dpeaa)DE-He213 Zalesky, B. A. aut Ablameyko, S. V. aut Enthalten in Pattern recognition and image analysis Moscow : MAIK Nauka/Interperiodica Publ., 1996 21(2011), 3 vom: 13. Sept. (DE-627)327148179 (DE-600)2044032-7 1555-6212 nnns volume:21 year:2011 number:3 day:13 month:09 https://dx.doi.org/10.1134/S1054661811020696 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 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_4126 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 21 2011 3 13 09
allfieldsGer	10.1134/S1054661811020696 doi (DE-627)SPR020176368 (SPR)S1054661811020696-e DE-627 ger DE-627 rakwb eng Lukashevich, P. V. verfasserin aut Medical image registration based on SURF detector 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2011 Abstract A quick method of 2D global registration of CT images in different series of studies of one patient is suggested in this work. The distinguishing feature of this approach is the use of image registration based on the SURF (Speeded Up Robust Features) detector, which has proved efficient in computer vision. Image Registration (dpeaa)DE-He213 Robust Feature (dpeaa)DE-He213 DICOM Image (dpeaa)DE-He213 Perspective Transformation (dpeaa)DE-He213 Medical Image Registration (dpeaa)DE-He213 Zalesky, B. A. aut Ablameyko, S. V. aut Enthalten in Pattern recognition and image analysis Moscow : MAIK Nauka/Interperiodica Publ., 1996 21(2011), 3 vom: 13. Sept. (DE-627)327148179 (DE-600)2044032-7 1555-6212 nnns volume:21 year:2011 number:3 day:13 month:09 https://dx.doi.org/10.1134/S1054661811020696 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 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_4126 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 21 2011 3 13 09
allfieldsSound	10.1134/S1054661811020696 doi (DE-627)SPR020176368 (SPR)S1054661811020696-e DE-627 ger DE-627 rakwb eng Lukashevich, P. V. verfasserin aut Medical image registration based on SURF detector 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Pleiades Publishing, Ltd. 2011 Abstract A quick method of 2D global registration of CT images in different series of studies of one patient is suggested in this work. The distinguishing feature of this approach is the use of image registration based on the SURF (Speeded Up Robust Features) detector, which has proved efficient in computer vision. Image Registration (dpeaa)DE-He213 Robust Feature (dpeaa)DE-He213 DICOM Image (dpeaa)DE-He213 Perspective Transformation (dpeaa)DE-He213 Medical Image Registration (dpeaa)DE-He213 Zalesky, B. A. aut Ablameyko, S. V. aut Enthalten in Pattern recognition and image analysis Moscow : MAIK Nauka/Interperiodica Publ., 1996 21(2011), 3 vom: 13. Sept. (DE-627)327148179 (DE-600)2044032-7 1555-6212 nnns volume:21 year:2011 number:3 day:13 month:09 https://dx.doi.org/10.1134/S1054661811020696 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 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_4126 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 21 2011 3 13 09
language	English
source	Enthalten in Pattern recognition and image analysis 21(2011), 3 vom: 13. Sept. volume:21 year:2011 number:3 day:13 month:09
sourceStr	Enthalten in Pattern recognition and image analysis 21(2011), 3 vom: 13. Sept. volume:21 year:2011 number:3 day:13 month:09
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Image Registration Robust Feature DICOM Image Perspective Transformation Medical Image Registration
isfreeaccess_bool	false
container_title	Pattern recognition and image analysis
authorswithroles_txt_mv	Lukashevich, P. V. @@aut@@ Zalesky, B. A. @@aut@@ Ablameyko, S. V. @@aut@@
publishDateDaySort_date	2011-09-13T00:00:00Z
hierarchy_top_id	327148179
id	SPR020176368
language_de	englisch
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author	Lukashevich, P. V.
spellingShingle	Lukashevich, P. V. misc Image Registration misc Robust Feature misc DICOM Image misc Perspective Transformation misc Medical Image Registration Medical image registration based on SURF detector
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topic_title	Medical image registration based on SURF detector Image Registration (dpeaa)DE-He213 Robust Feature (dpeaa)DE-He213 DICOM Image (dpeaa)DE-He213 Perspective Transformation (dpeaa)DE-He213 Medical Image Registration (dpeaa)DE-He213
topic	misc Image Registration misc Robust Feature misc DICOM Image misc Perspective Transformation misc Medical Image Registration
topic_unstemmed	misc Image Registration misc Robust Feature misc DICOM Image misc Perspective Transformation misc Medical Image Registration
topic_browse	misc Image Registration misc Robust Feature misc DICOM Image misc Perspective Transformation misc Medical Image Registration
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title	Medical image registration based on SURF detector
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title_full	Medical image registration based on SURF detector
author_sort	Lukashevich, P. V.
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author_browse	Lukashevich, P. V. Zalesky, B. A. Ablameyko, S. V.
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title_sort	medical image registration based on surf detector
title_auth	Medical image registration based on SURF detector
abstract	Abstract A quick method of 2D global registration of CT images in different series of studies of one patient is suggested in this work. The distinguishing feature of this approach is the use of image registration based on the SURF (Speeded Up Robust Features) detector, which has proved efficient in computer vision. © Pleiades Publishing, Ltd. 2011
abstractGer	Abstract A quick method of 2D global registration of CT images in different series of studies of one patient is suggested in this work. The distinguishing feature of this approach is the use of image registration based on the SURF (Speeded Up Robust Features) detector, which has proved efficient in computer vision. © Pleiades Publishing, Ltd. 2011
abstract_unstemmed	Abstract A quick method of 2D global registration of CT images in different series of studies of one patient is suggested in this work. The distinguishing feature of this approach is the use of image registration based on the SURF (Speeded Up Robust Features) detector, which has proved efficient in computer vision. © Pleiades Publishing, Ltd. 2011
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title_short	Medical image registration based on SURF detector
url	https://dx.doi.org/10.1134/S1054661811020696
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author2	Zalesky, B. A. Ablameyko, S. V.
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up_date	2024-07-03T14:22:22.615Z
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V.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Medical image registration based on SURF detector</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2011</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">© Pleiades Publishing, Ltd. 2011</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract A quick method of 2D global registration of CT images in different series of studies of one patient is suggested in this work. The distinguishing feature of this approach is the use of image registration based on the SURF (Speeded Up Robust Features) detector, which has proved efficient in computer vision.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Image Registration</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Robust Feature</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">DICOM Image</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Perspective Transformation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Medical Image Registration</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zalesky, B. A.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ablameyko, S. V.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Pattern recognition and image analysis</subfield><subfield code="d">Moscow : MAIK Nauka/Interperiodica Publ., 1996</subfield><subfield code="g">21(2011), 3 vom: 13. 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