Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy

The objective of this study was to investigate the diagnosis of colonic polyps (CP) through the computed tomography (CT) images combined with colonoscopy based on Fourier central slice theorem algorithm. In this study, 86 patients with CP admitted to hospital were selected as research objects. CT im...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Xiangyan Guo [verfasserIn] Hui Gao [verfasserIn] Xiaofang Sun [verfasserIn] Surong Li [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Übergeordnetes Werk:	In: Scientific Programming - Hindawi Limited, 2015, (2021)
Übergeordnetes Werk:	year:2021

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1155/2021/1238805

Katalog-ID:	DOAJ07294272X

Internformat


LEADER	01000naa a22002652 4500
001	DOAJ07294272X
003	DE-627
005	20230228112505.0
007	cr uuu---uuuuu
008	230228s2021 xx \|\|\|\|\|o 00\| \|\|eng c
024	7		\|a 10.1155/2021/1238805 \|2 doi
035			\|a (DE-627)DOAJ07294272X
035			\|a (DE-599)DOAJd003bb13e0d94f7cb7f3704c27d8af5b
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
050		0	\|a QA76.75-76.765
100	0		\|a Xiangyan Guo \|e verfasserin \|4 aut
245	1	0	\|a Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy
264		1	\|c 2021
336			\|a Text \|b txt \|2 rdacontent
337			\|a Computermedien \|b c \|2 rdamedia
338			\|a Online-Ressource \|b cr \|2 rdacarrier
520			\|a The objective of this study was to investigate the diagnosis of colonic polyps (CP) through the computed tomography (CT) images combined with colonoscopy based on Fourier central slice theorem algorithm. In this study, 86 patients with CP admitted to hospital were selected as research objects. CT imaging and colonoscopy were applied to diagnose the patients based on the algorithm of Fourier central slice theorem. The results showed that the diagnostic detection rates of CP and colon cancer (CC) were 88.2% and 94.2%, respectively. The occurrence site of CP was the sigmoid and ascending colon. 38 patients were positive for serosal invasion of CP while 42 patients were negative for serosal invasion of CP, and there were no statistical differences (P<0.05). The lesion positions of remaining 6 cases were hard to find and could not be detected accurately. Besides, the diagnostic accuracy of preoperative and postoperative stages III and IV was all 100.00%. The combination of CT imaging and colonoscopy was employed to diagnose CP, which was found to be able to accurately locate the lesions, to effectively evaluate the tumor stage before and after surgery, and to have a good diagnostic efficacy in detecting tumor serosal layer.
653		0	\|a Computer software
700	0		\|a Hui Gao \|e verfasserin \|4 aut
700	0		\|a Xiaofang Sun \|e verfasserin \|4 aut
700	0		\|a Surong Li \|e verfasserin \|4 aut
773	0	8	\|i In \|t Scientific Programming \|d Hindawi Limited, 2015 \|g (2021) \|w (DE-627)34190242X \|w (DE-600)2070004-0 \|x 10589244 \|7 nnns
773	1	8	\|g year:2021
856	4	0	\|u https://doi.org/10.1155/2021/1238805 \|z kostenfrei
856	4	0	\|u https://doaj.org/article/d003bb13e0d94f7cb7f3704c27d8af5b \|z kostenfrei
856	4	0	\|u http://dx.doi.org/10.1155/2021/1238805 \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/1058-9244 \|y Journal toc \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/1875-919X \|y Journal toc \|z kostenfrei
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_DOAJ
912			\|a GBV_ILN_11
912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_31
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_95
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_151
912			\|a GBV_ILN_161
912			\|a GBV_ILN_165
912			\|a GBV_ILN_170
912			\|a GBV_ILN_171
912			\|a GBV_ILN_206
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_636
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2007
912			\|a GBV_ILN_2008
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2026
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2031
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2037
912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2108
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2118
912			\|a GBV_ILN_2119
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2144
912			\|a GBV_ILN_2147
912			\|a GBV_ILN_2148
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2470
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4242
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4251
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4336
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4392
912			\|a GBV_ILN_4700
951			\|a AR
952			\|j 2021

Indexfelder

author_variant	x g xg h g hg x s xs s l sl
matchkey_str	article:10589244:2021----::eperigodtcinfooiplpfocmuetmgahclnsoym
hierarchy_sort_str	2021
callnumber-subject-code	QA
publishDate	2021
allfields	10.1155/2021/1238805 doi (DE-627)DOAJ07294272X (DE-599)DOAJd003bb13e0d94f7cb7f3704c27d8af5b DE-627 ger DE-627 rakwb eng QA76.75-76.765 Xiangyan Guo verfasserin aut Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The objective of this study was to investigate the diagnosis of colonic polyps (CP) through the computed tomography (CT) images combined with colonoscopy based on Fourier central slice theorem algorithm. In this study, 86 patients with CP admitted to hospital were selected as research objects. CT imaging and colonoscopy were applied to diagnose the patients based on the algorithm of Fourier central slice theorem. The results showed that the diagnostic detection rates of CP and colon cancer (CC) were 88.2% and 94.2%, respectively. The occurrence site of CP was the sigmoid and ascending colon. 38 patients were positive for serosal invasion of CP while 42 patients were negative for serosal invasion of CP, and there were no statistical differences (P<0.05). The lesion positions of remaining 6 cases were hard to find and could not be detected accurately. Besides, the diagnostic accuracy of preoperative and postoperative stages III and IV was all 100.00%. The combination of CT imaging and colonoscopy was employed to diagnose CP, which was found to be able to accurately locate the lesions, to effectively evaluate the tumor stage before and after surgery, and to have a good diagnostic efficacy in detecting tumor serosal layer. Computer software Hui Gao verfasserin aut Xiaofang Sun verfasserin aut Surong Li verfasserin aut In Scientific Programming Hindawi Limited, 2015 (2021) (DE-627)34190242X (DE-600)2070004-0 10589244 nnns year:2021 https://doi.org/10.1155/2021/1238805 kostenfrei https://doaj.org/article/d003bb13e0d94f7cb7f3704c27d8af5b kostenfrei http://dx.doi.org/10.1155/2021/1238805 kostenfrei https://doaj.org/toc/1058-9244 Journal toc kostenfrei https://doaj.org/toc/1875-919X 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_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 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_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2021
spelling	10.1155/2021/1238805 doi (DE-627)DOAJ07294272X (DE-599)DOAJd003bb13e0d94f7cb7f3704c27d8af5b DE-627 ger DE-627 rakwb eng QA76.75-76.765 Xiangyan Guo verfasserin aut Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The objective of this study was to investigate the diagnosis of colonic polyps (CP) through the computed tomography (CT) images combined with colonoscopy based on Fourier central slice theorem algorithm. In this study, 86 patients with CP admitted to hospital were selected as research objects. CT imaging and colonoscopy were applied to diagnose the patients based on the algorithm of Fourier central slice theorem. The results showed that the diagnostic detection rates of CP and colon cancer (CC) were 88.2% and 94.2%, respectively. The occurrence site of CP was the sigmoid and ascending colon. 38 patients were positive for serosal invasion of CP while 42 patients were negative for serosal invasion of CP, and there were no statistical differences (P<0.05). The lesion positions of remaining 6 cases were hard to find and could not be detected accurately. Besides, the diagnostic accuracy of preoperative and postoperative stages III and IV was all 100.00%. The combination of CT imaging and colonoscopy was employed to diagnose CP, which was found to be able to accurately locate the lesions, to effectively evaluate the tumor stage before and after surgery, and to have a good diagnostic efficacy in detecting tumor serosal layer. Computer software Hui Gao verfasserin aut Xiaofang Sun verfasserin aut Surong Li verfasserin aut In Scientific Programming Hindawi Limited, 2015 (2021) (DE-627)34190242X (DE-600)2070004-0 10589244 nnns year:2021 https://doi.org/10.1155/2021/1238805 kostenfrei https://doaj.org/article/d003bb13e0d94f7cb7f3704c27d8af5b kostenfrei http://dx.doi.org/10.1155/2021/1238805 kostenfrei https://doaj.org/toc/1058-9244 Journal toc kostenfrei https://doaj.org/toc/1875-919X 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_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 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_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2021
allfields_unstemmed	10.1155/2021/1238805 doi (DE-627)DOAJ07294272X (DE-599)DOAJd003bb13e0d94f7cb7f3704c27d8af5b DE-627 ger DE-627 rakwb eng QA76.75-76.765 Xiangyan Guo verfasserin aut Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The objective of this study was to investigate the diagnosis of colonic polyps (CP) through the computed tomography (CT) images combined with colonoscopy based on Fourier central slice theorem algorithm. In this study, 86 patients with CP admitted to hospital were selected as research objects. CT imaging and colonoscopy were applied to diagnose the patients based on the algorithm of Fourier central slice theorem. The results showed that the diagnostic detection rates of CP and colon cancer (CC) were 88.2% and 94.2%, respectively. The occurrence site of CP was the sigmoid and ascending colon. 38 patients were positive for serosal invasion of CP while 42 patients were negative for serosal invasion of CP, and there were no statistical differences (P<0.05). The lesion positions of remaining 6 cases were hard to find and could not be detected accurately. Besides, the diagnostic accuracy of preoperative and postoperative stages III and IV was all 100.00%. The combination of CT imaging and colonoscopy was employed to diagnose CP, which was found to be able to accurately locate the lesions, to effectively evaluate the tumor stage before and after surgery, and to have a good diagnostic efficacy in detecting tumor serosal layer. Computer software Hui Gao verfasserin aut Xiaofang Sun verfasserin aut Surong Li verfasserin aut In Scientific Programming Hindawi Limited, 2015 (2021) (DE-627)34190242X (DE-600)2070004-0 10589244 nnns year:2021 https://doi.org/10.1155/2021/1238805 kostenfrei https://doaj.org/article/d003bb13e0d94f7cb7f3704c27d8af5b kostenfrei http://dx.doi.org/10.1155/2021/1238805 kostenfrei https://doaj.org/toc/1058-9244 Journal toc kostenfrei https://doaj.org/toc/1875-919X 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_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 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_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2021
allfieldsGer	10.1155/2021/1238805 doi (DE-627)DOAJ07294272X (DE-599)DOAJd003bb13e0d94f7cb7f3704c27d8af5b DE-627 ger DE-627 rakwb eng QA76.75-76.765 Xiangyan Guo verfasserin aut Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The objective of this study was to investigate the diagnosis of colonic polyps (CP) through the computed tomography (CT) images combined with colonoscopy based on Fourier central slice theorem algorithm. In this study, 86 patients with CP admitted to hospital were selected as research objects. CT imaging and colonoscopy were applied to diagnose the patients based on the algorithm of Fourier central slice theorem. The results showed that the diagnostic detection rates of CP and colon cancer (CC) were 88.2% and 94.2%, respectively. The occurrence site of CP was the sigmoid and ascending colon. 38 patients were positive for serosal invasion of CP while 42 patients were negative for serosal invasion of CP, and there were no statistical differences (P<0.05). The lesion positions of remaining 6 cases were hard to find and could not be detected accurately. Besides, the diagnostic accuracy of preoperative and postoperative stages III and IV was all 100.00%. The combination of CT imaging and colonoscopy was employed to diagnose CP, which was found to be able to accurately locate the lesions, to effectively evaluate the tumor stage before and after surgery, and to have a good diagnostic efficacy in detecting tumor serosal layer. Computer software Hui Gao verfasserin aut Xiaofang Sun verfasserin aut Surong Li verfasserin aut In Scientific Programming Hindawi Limited, 2015 (2021) (DE-627)34190242X (DE-600)2070004-0 10589244 nnns year:2021 https://doi.org/10.1155/2021/1238805 kostenfrei https://doaj.org/article/d003bb13e0d94f7cb7f3704c27d8af5b kostenfrei http://dx.doi.org/10.1155/2021/1238805 kostenfrei https://doaj.org/toc/1058-9244 Journal toc kostenfrei https://doaj.org/toc/1875-919X 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_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 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_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2021
allfieldsSound	10.1155/2021/1238805 doi (DE-627)DOAJ07294272X (DE-599)DOAJd003bb13e0d94f7cb7f3704c27d8af5b DE-627 ger DE-627 rakwb eng QA76.75-76.765 Xiangyan Guo verfasserin aut Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The objective of this study was to investigate the diagnosis of colonic polyps (CP) through the computed tomography (CT) images combined with colonoscopy based on Fourier central slice theorem algorithm. In this study, 86 patients with CP admitted to hospital were selected as research objects. CT imaging and colonoscopy were applied to diagnose the patients based on the algorithm of Fourier central slice theorem. The results showed that the diagnostic detection rates of CP and colon cancer (CC) were 88.2% and 94.2%, respectively. The occurrence site of CP was the sigmoid and ascending colon. 38 patients were positive for serosal invasion of CP while 42 patients were negative for serosal invasion of CP, and there were no statistical differences (P<0.05). The lesion positions of remaining 6 cases were hard to find and could not be detected accurately. Besides, the diagnostic accuracy of preoperative and postoperative stages III and IV was all 100.00%. The combination of CT imaging and colonoscopy was employed to diagnose CP, which was found to be able to accurately locate the lesions, to effectively evaluate the tumor stage before and after surgery, and to have a good diagnostic efficacy in detecting tumor serosal layer. Computer software Hui Gao verfasserin aut Xiaofang Sun verfasserin aut Surong Li verfasserin aut In Scientific Programming Hindawi Limited, 2015 (2021) (DE-627)34190242X (DE-600)2070004-0 10589244 nnns year:2021 https://doi.org/10.1155/2021/1238805 kostenfrei https://doaj.org/article/d003bb13e0d94f7cb7f3704c27d8af5b kostenfrei http://dx.doi.org/10.1155/2021/1238805 kostenfrei https://doaj.org/toc/1058-9244 Journal toc kostenfrei https://doaj.org/toc/1875-919X 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_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 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_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2021
language	English
source	In Scientific Programming (2021) year:2021
sourceStr	In Scientific Programming (2021) year:2021
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Computer software
isfreeaccess_bool	true
container_title	Scientific Programming
authorswithroles_txt_mv	Xiangyan Guo @@aut@@ Hui Gao @@aut@@ Xiaofang Sun @@aut@@ Surong Li @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	34190242X
id	DOAJ07294272X
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ07294272X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230228112505.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230228s2021 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1155/2021/1238805</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ07294272X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJd003bb13e0d94f7cb7f3704c27d8af5b</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="050" ind1=" " ind2="0"><subfield code="a">QA76.75-76.765</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Xiangyan Guo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</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="520" ind1=" " ind2=" "><subfield code="a">The objective of this study was to investigate the diagnosis of colonic polyps (CP) through the computed tomography (CT) images combined with colonoscopy based on Fourier central slice theorem algorithm. In this study, 86 patients with CP admitted to hospital were selected as research objects. CT imaging and colonoscopy were applied to diagnose the patients based on the algorithm of Fourier central slice theorem. The results showed that the diagnostic detection rates of CP and colon cancer (CC) were 88.2% and 94.2%, respectively. The occurrence site of CP was the sigmoid and ascending colon. 38 patients were positive for serosal invasion of CP while 42 patients were negative for serosal invasion of CP, and there were no statistical differences (P<0.05). The lesion positions of remaining 6 cases were hard to find and could not be detected accurately. Besides, the diagnostic accuracy of preoperative and postoperative stages III and IV was all 100.00%. The combination of CT imaging and colonoscopy was employed to diagnose CP, which was found to be able to accurately locate the lesions, to effectively evaluate the tumor stage before and after surgery, and to have a good diagnostic efficacy in detecting tumor serosal layer.</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Computer software</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Hui Gao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Xiaofang Sun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Surong Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Scientific Programming</subfield><subfield code="d">Hindawi Limited, 2015</subfield><subfield code="g">(2021)</subfield><subfield code="w">(DE-627)34190242X</subfield><subfield code="w">(DE-600)2070004-0</subfield><subfield code="x">10589244</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">year:2021</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1155/2021/1238805</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/d003bb13e0d94f7cb7f3704c27d8af5b</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://dx.doi.org/10.1155/2021/1238805</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1058-9244</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1875-919X</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</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_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_165</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_636</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2007</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2010</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2026</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2031</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2056</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2057</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2068</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2106</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2108</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2118</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2119</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2144</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2147</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2148</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2232</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2470</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2522</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4392</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="j">2021</subfield></datafield></record></collection>
callnumber-first	Q - Science
author	Xiangyan Guo
spellingShingle	Xiangyan Guo misc QA76.75-76.765 misc Computer software Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy
authorStr	Xiangyan Guo
ppnlink_with_tag_str_mv	@@773@@(DE-627)34190242X
format	electronic Article
delete_txt_mv	keep
author_role	aut aut aut aut
collection	DOAJ
remote_str	true
callnumber-label	QA76
illustrated	Not Illustrated
issn	10589244
topic_title	QA76.75-76.765 Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy
topic	misc QA76.75-76.765 misc Computer software
topic_unstemmed	misc QA76.75-76.765 misc Computer software
topic_browse	misc QA76.75-76.765 misc Computer software
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	cr
hierarchy_parent_title	Scientific Programming
hierarchy_parent_id	34190242X
hierarchy_top_title	Scientific Programming
isfreeaccess_txt	true
familylinks_str_mv	(DE-627)34190242X (DE-600)2070004-0
title	Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy
ctrlnum	(DE-627)DOAJ07294272X (DE-599)DOAJd003bb13e0d94f7cb7f3704c27d8af5b
title_full	Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy
author_sort	Xiangyan Guo
journal	Scientific Programming
journalStr	Scientific Programming
callnumber-first-code	Q
lang_code	eng
isOA_bool	true
recordtype	marc
publishDateSort	2021
contenttype_str_mv	txt
author_browse	Xiangyan Guo Hui Gao Xiaofang Sun Surong Li
class	QA76.75-76.765
format_se	Elektronische Aufsätze
author-letter	Xiangyan Guo
doi_str_mv	10.1155/2021/1238805
author2-role	verfasserin
title_sort	deep learning for detection of colonic polyps from computed tomography colonoscopy images combined with colonoscopy
callnumber	QA76.75-76.765
title_auth	Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy
abstract	The objective of this study was to investigate the diagnosis of colonic polyps (CP) through the computed tomography (CT) images combined with colonoscopy based on Fourier central slice theorem algorithm. In this study, 86 patients with CP admitted to hospital were selected as research objects. CT imaging and colonoscopy were applied to diagnose the patients based on the algorithm of Fourier central slice theorem. The results showed that the diagnostic detection rates of CP and colon cancer (CC) were 88.2% and 94.2%, respectively. The occurrence site of CP was the sigmoid and ascending colon. 38 patients were positive for serosal invasion of CP while 42 patients were negative for serosal invasion of CP, and there were no statistical differences (P<0.05). The lesion positions of remaining 6 cases were hard to find and could not be detected accurately. Besides, the diagnostic accuracy of preoperative and postoperative stages III and IV was all 100.00%. The combination of CT imaging and colonoscopy was employed to diagnose CP, which was found to be able to accurately locate the lesions, to effectively evaluate the tumor stage before and after surgery, and to have a good diagnostic efficacy in detecting tumor serosal layer.
abstractGer	The objective of this study was to investigate the diagnosis of colonic polyps (CP) through the computed tomography (CT) images combined with colonoscopy based on Fourier central slice theorem algorithm. In this study, 86 patients with CP admitted to hospital were selected as research objects. CT imaging and colonoscopy were applied to diagnose the patients based on the algorithm of Fourier central slice theorem. The results showed that the diagnostic detection rates of CP and colon cancer (CC) were 88.2% and 94.2%, respectively. The occurrence site of CP was the sigmoid and ascending colon. 38 patients were positive for serosal invasion of CP while 42 patients were negative for serosal invasion of CP, and there were no statistical differences (P<0.05). The lesion positions of remaining 6 cases were hard to find and could not be detected accurately. Besides, the diagnostic accuracy of preoperative and postoperative stages III and IV was all 100.00%. The combination of CT imaging and colonoscopy was employed to diagnose CP, which was found to be able to accurately locate the lesions, to effectively evaluate the tumor stage before and after surgery, and to have a good diagnostic efficacy in detecting tumor serosal layer.
abstract_unstemmed	The objective of this study was to investigate the diagnosis of colonic polyps (CP) through the computed tomography (CT) images combined with colonoscopy based on Fourier central slice theorem algorithm. In this study, 86 patients with CP admitted to hospital were selected as research objects. CT imaging and colonoscopy were applied to diagnose the patients based on the algorithm of Fourier central slice theorem. The results showed that the diagnostic detection rates of CP and colon cancer (CC) were 88.2% and 94.2%, respectively. The occurrence site of CP was the sigmoid and ascending colon. 38 patients were positive for serosal invasion of CP while 42 patients were negative for serosal invasion of CP, and there were no statistical differences (P<0.05). The lesion positions of remaining 6 cases were hard to find and could not be detected accurately. Besides, the diagnostic accuracy of preoperative and postoperative stages III and IV was all 100.00%. The combination of CT imaging and colonoscopy was employed to diagnose CP, which was found to be able to accurately locate the lesions, to effectively evaluate the tumor stage before and after surgery, and to have a good diagnostic efficacy in detecting tumor serosal layer.
collection_details	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_165 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 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_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 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_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700
title_short	Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy
url	https://doi.org/10.1155/2021/1238805 https://doaj.org/article/d003bb13e0d94f7cb7f3704c27d8af5b http://dx.doi.org/10.1155/2021/1238805 https://doaj.org/toc/1058-9244 https://doaj.org/toc/1875-919X
remote_bool	true
author2	Hui Gao Xiaofang Sun Surong Li
author2Str	Hui Gao Xiaofang Sun Surong Li
ppnlink	34190242X
callnumber-subject	QA - Mathematics
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	false
doi_str	10.1155/2021/1238805
callnumber-a	QA76.75-76.765
up_date	2024-07-03T14:56:42.580Z
_version_	1803570226223120384
fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ07294272X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230228112505.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230228s2021 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1155/2021/1238805</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ07294272X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJd003bb13e0d94f7cb7f3704c27d8af5b</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="050" ind1=" " ind2="0"><subfield code="a">QA76.75-76.765</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Xiangyan Guo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</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="520" ind1=" " ind2=" "><subfield code="a">The objective of this study was to investigate the diagnosis of colonic polyps (CP) through the computed tomography (CT) images combined with colonoscopy based on Fourier central slice theorem algorithm. In this study, 86 patients with CP admitted to hospital were selected as research objects. CT imaging and colonoscopy were applied to diagnose the patients based on the algorithm of Fourier central slice theorem. The results showed that the diagnostic detection rates of CP and colon cancer (CC) were 88.2% and 94.2%, respectively. The occurrence site of CP was the sigmoid and ascending colon. 38 patients were positive for serosal invasion of CP while 42 patients were negative for serosal invasion of CP, and there were no statistical differences (P<0.05). The lesion positions of remaining 6 cases were hard to find and could not be detected accurately. Besides, the diagnostic accuracy of preoperative and postoperative stages III and IV was all 100.00%. The combination of CT imaging and colonoscopy was employed to diagnose CP, which was found to be able to accurately locate the lesions, to effectively evaluate the tumor stage before and after surgery, and to have a good diagnostic efficacy in detecting tumor serosal layer.</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Computer software</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Hui Gao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Xiaofang Sun</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Surong Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Scientific Programming</subfield><subfield code="d">Hindawi Limited, 2015</subfield><subfield code="g">(2021)</subfield><subfield code="w">(DE-627)34190242X</subfield><subfield code="w">(DE-600)2070004-0</subfield><subfield code="x">10589244</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">year:2021</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1155/2021/1238805</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/d003bb13e0d94f7cb7f3704c27d8af5b</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://dx.doi.org/10.1155/2021/1238805</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1058-9244</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1875-919X</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</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_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_165</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_636</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_702</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2003</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2007</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2010</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2011</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2020</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2025</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2026</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2027</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2031</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2034</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2038</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2044</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2048</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2050</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2055</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2056</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2057</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2059</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2061</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2068</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2088</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2106</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2108</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2111</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2118</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2119</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2122</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2143</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2144</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2147</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2148</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2152</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2190</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2232</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2470</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2507</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2522</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4035</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4242</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4251</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4326</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4334</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4336</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4392</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="j">2021</subfield></datafield></record></collection>
score	7.400278

Nicht das Richtige dabei?

Schreiben Sie uns!

Deep Learning for Detection of Colonic Polyps from Computed Tomography Colonoscopy Images Combined with Colonoscopy

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?