Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis

The technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnost...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Abhishek Banerjee [verfasserIn] Venkatesh V Kamath [verfasserIn] R M Lavanya [verfasserIn] S K Shruthi [verfasserIn] M Deepa [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2015

Schlagwörter:	Diagnostic algorithms digitization mathematical algorithms oral histopathology

Übergeordnetes Werk:	In: Journal of Dental Research and Review - Wolters Kluwer Medknow Publications, 2017, 2(2015), 2, Seite 97-101
Übergeordnetes Werk:	volume:2 ; year:2015 ; number:2 ; pages:97-101

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

DOI / URN:	10.4103/2348-2915.161216

Katalog-ID:	DOAJ055658954

Internformat


LEADER	01000caa a22002652 4500
001	DOAJ055658954
003	DE-627
005	20230502090854.0
007	cr uuu---uuuuu
008	230227s2015 xx \|\|\|\|\|o 00\| \|\|eng c
024	7		\|a 10.4103/2348-2915.161216 \|2 doi
035			\|a (DE-627)DOAJ055658954
035			\|a (DE-599)DOAJ303cae508c8042368b9d5eea50ae15d3
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
050		0	\|a RK1-715
100	0		\|a Abhishek Banerjee \|e verfasserin \|4 aut
245	1	0	\|a Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis
264		1	\|c 2015
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 technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms) include both object based (object features, structures) and pixel based (texture) measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms) in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis.
650		4	\|a Diagnostic algorithms
650		4	\|a digitization
650		4	\|a mathematical algorithms
650		4	\|a oral histopathology
653		0	\|a Dentistry
700	0		\|a Venkatesh V Kamath \|e verfasserin \|4 aut
700	0		\|a R M Lavanya \|e verfasserin \|4 aut
700	0		\|a S K Shruthi \|e verfasserin \|4 aut
700	0		\|a M Deepa \|e verfasserin \|4 aut
773	0	8	\|i In \|t Journal of Dental Research and Review \|d Wolters Kluwer Medknow Publications, 2017 \|g 2(2015), 2, Seite 97-101 \|w (DE-627)1725660016 \|x 23483172 \|7 nnns
773	1	8	\|g volume:2 \|g year:2015 \|g number:2 \|g pages:97-101
856	4	0	\|u https://doi.org/10.4103/2348-2915.161216 \|z kostenfrei
856	4	0	\|u https://doaj.org/article/303cae508c8042368b9d5eea50ae15d3 \|z kostenfrei
856	4	0	\|u http://www.jdrr.org/article.asp?issn=2348-2915;year=2015;volume=2;issue=2;spage=97;epage=101;aulast=Banerjee \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/2348-2915 \|y Journal toc \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/2348-3172 \|y Journal toc \|z kostenfrei
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_DOAJ
912			\|a SSG-OLC-PHA
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_73
912			\|a GBV_ILN_74
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_170
912			\|a GBV_ILN_206
912			\|a GBV_ILN_213
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_602
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4249
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_4338
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4700
951			\|a AR
952			\|d 2 \|j 2015 \|e 2 \|h 97-101

Indexfelder

author_variant	a b ab v v k vvk r m l rml s k s sks m d md
matchkey_str	article:23483172:2015----::ahmtcligotcloihsnhdgtztoooahsoahlgteefot
hierarchy_sort_str	2015
callnumber-subject-code	RK
publishDate	2015
allfields	10.4103/2348-2915.161216 doi (DE-627)DOAJ055658954 (DE-599)DOAJ303cae508c8042368b9d5eea50ae15d3 DE-627 ger DE-627 rakwb eng RK1-715 Abhishek Banerjee verfasserin aut Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms) include both object based (object features, structures) and pixel based (texture) measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms) in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis. Diagnostic algorithms digitization mathematical algorithms oral histopathology Dentistry Venkatesh V Kamath verfasserin aut R M Lavanya verfasserin aut S K Shruthi verfasserin aut M Deepa verfasserin aut In Journal of Dental Research and Review Wolters Kluwer Medknow Publications, 2017 2(2015), 2, Seite 97-101 (DE-627)1725660016 23483172 nnns volume:2 year:2015 number:2 pages:97-101 https://doi.org/10.4103/2348-2915.161216 kostenfrei https://doaj.org/article/303cae508c8042368b9d5eea50ae15d3 kostenfrei http://www.jdrr.org/article.asp?issn=2348-2915;year=2015;volume=2;issue=2;spage=97;epage=101;aulast=Banerjee kostenfrei https://doaj.org/toc/2348-2915 Journal toc kostenfrei https://doaj.org/toc/2348-3172 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2015 2 97-101
spelling	10.4103/2348-2915.161216 doi (DE-627)DOAJ055658954 (DE-599)DOAJ303cae508c8042368b9d5eea50ae15d3 DE-627 ger DE-627 rakwb eng RK1-715 Abhishek Banerjee verfasserin aut Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms) include both object based (object features, structures) and pixel based (texture) measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms) in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis. Diagnostic algorithms digitization mathematical algorithms oral histopathology Dentistry Venkatesh V Kamath verfasserin aut R M Lavanya verfasserin aut S K Shruthi verfasserin aut M Deepa verfasserin aut In Journal of Dental Research and Review Wolters Kluwer Medknow Publications, 2017 2(2015), 2, Seite 97-101 (DE-627)1725660016 23483172 nnns volume:2 year:2015 number:2 pages:97-101 https://doi.org/10.4103/2348-2915.161216 kostenfrei https://doaj.org/article/303cae508c8042368b9d5eea50ae15d3 kostenfrei http://www.jdrr.org/article.asp?issn=2348-2915;year=2015;volume=2;issue=2;spage=97;epage=101;aulast=Banerjee kostenfrei https://doaj.org/toc/2348-2915 Journal toc kostenfrei https://doaj.org/toc/2348-3172 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2015 2 97-101
allfields_unstemmed	10.4103/2348-2915.161216 doi (DE-627)DOAJ055658954 (DE-599)DOAJ303cae508c8042368b9d5eea50ae15d3 DE-627 ger DE-627 rakwb eng RK1-715 Abhishek Banerjee verfasserin aut Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms) include both object based (object features, structures) and pixel based (texture) measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms) in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis. Diagnostic algorithms digitization mathematical algorithms oral histopathology Dentistry Venkatesh V Kamath verfasserin aut R M Lavanya verfasserin aut S K Shruthi verfasserin aut M Deepa verfasserin aut In Journal of Dental Research and Review Wolters Kluwer Medknow Publications, 2017 2(2015), 2, Seite 97-101 (DE-627)1725660016 23483172 nnns volume:2 year:2015 number:2 pages:97-101 https://doi.org/10.4103/2348-2915.161216 kostenfrei https://doaj.org/article/303cae508c8042368b9d5eea50ae15d3 kostenfrei http://www.jdrr.org/article.asp?issn=2348-2915;year=2015;volume=2;issue=2;spage=97;epage=101;aulast=Banerjee kostenfrei https://doaj.org/toc/2348-2915 Journal toc kostenfrei https://doaj.org/toc/2348-3172 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2015 2 97-101
allfieldsGer	10.4103/2348-2915.161216 doi (DE-627)DOAJ055658954 (DE-599)DOAJ303cae508c8042368b9d5eea50ae15d3 DE-627 ger DE-627 rakwb eng RK1-715 Abhishek Banerjee verfasserin aut Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms) include both object based (object features, structures) and pixel based (texture) measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms) in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis. Diagnostic algorithms digitization mathematical algorithms oral histopathology Dentistry Venkatesh V Kamath verfasserin aut R M Lavanya verfasserin aut S K Shruthi verfasserin aut M Deepa verfasserin aut In Journal of Dental Research and Review Wolters Kluwer Medknow Publications, 2017 2(2015), 2, Seite 97-101 (DE-627)1725660016 23483172 nnns volume:2 year:2015 number:2 pages:97-101 https://doi.org/10.4103/2348-2915.161216 kostenfrei https://doaj.org/article/303cae508c8042368b9d5eea50ae15d3 kostenfrei http://www.jdrr.org/article.asp?issn=2348-2915;year=2015;volume=2;issue=2;spage=97;epage=101;aulast=Banerjee kostenfrei https://doaj.org/toc/2348-2915 Journal toc kostenfrei https://doaj.org/toc/2348-3172 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2015 2 97-101
allfieldsSound	10.4103/2348-2915.161216 doi (DE-627)DOAJ055658954 (DE-599)DOAJ303cae508c8042368b9d5eea50ae15d3 DE-627 ger DE-627 rakwb eng RK1-715 Abhishek Banerjee verfasserin aut Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms) include both object based (object features, structures) and pixel based (texture) measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms) in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis. Diagnostic algorithms digitization mathematical algorithms oral histopathology Dentistry Venkatesh V Kamath verfasserin aut R M Lavanya verfasserin aut S K Shruthi verfasserin aut M Deepa verfasserin aut In Journal of Dental Research and Review Wolters Kluwer Medknow Publications, 2017 2(2015), 2, Seite 97-101 (DE-627)1725660016 23483172 nnns volume:2 year:2015 number:2 pages:97-101 https://doi.org/10.4103/2348-2915.161216 kostenfrei https://doaj.org/article/303cae508c8042368b9d5eea50ae15d3 kostenfrei http://www.jdrr.org/article.asp?issn=2348-2915;year=2015;volume=2;issue=2;spage=97;epage=101;aulast=Banerjee kostenfrei https://doaj.org/toc/2348-2915 Journal toc kostenfrei https://doaj.org/toc/2348-3172 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2015 2 97-101
language	English
source	In Journal of Dental Research and Review 2(2015), 2, Seite 97-101 volume:2 year:2015 number:2 pages:97-101
sourceStr	In Journal of Dental Research and Review 2(2015), 2, Seite 97-101 volume:2 year:2015 number:2 pages:97-101
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Diagnostic algorithms digitization mathematical algorithms oral histopathology Dentistry
isfreeaccess_bool	true
container_title	Journal of Dental Research and Review
authorswithroles_txt_mv	Abhishek Banerjee @@aut@@ Venkatesh V Kamath @@aut@@ R M Lavanya @@aut@@ S K Shruthi @@aut@@ M Deepa @@aut@@
publishDateDaySort_date	2015-01-01T00:00:00Z
hierarchy_top_id	1725660016
id	DOAJ055658954
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">DOAJ055658954</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502090854.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2015 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.4103/2348-2915.161216</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ055658954</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ303cae508c8042368b9d5eea50ae15d3</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">RK1-715</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Abhishek Banerjee</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</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 technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms) include both object based (object features, structures) and pixel based (texture) measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms) in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Diagnostic algorithms</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">digitization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">mathematical algorithms</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">oral histopathology</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Dentistry</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Venkatesh V Kamath</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">R M Lavanya</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">S K Shruthi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">M Deepa</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">Journal of Dental Research and Review</subfield><subfield code="d">Wolters Kluwer Medknow Publications, 2017</subfield><subfield code="g">2(2015), 2, Seite 97-101</subfield><subfield code="w">(DE-627)1725660016</subfield><subfield code="x">23483172</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:2</subfield><subfield code="g">year:2015</subfield><subfield code="g">number:2</subfield><subfield code="g">pages:97-101</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.4103/2348-2915.161216</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/303cae508c8042368b9d5eea50ae15d3</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://www.jdrr.org/article.asp?issn=2348-2915;year=2015;volume=2;issue=2;spage=97;epage=101;aulast=Banerjee</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2348-2915</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/2348-3172</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">SSG-OLC-PHA</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_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</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_170</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_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_602</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_4012</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_4249</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_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_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">2</subfield><subfield code="j">2015</subfield><subfield code="e">2</subfield><subfield code="h">97-101</subfield></datafield></record></collection>
callnumber-first	R - Medicine
author	Abhishek Banerjee
spellingShingle	Abhishek Banerjee misc RK1-715 misc Diagnostic algorithms misc digitization misc mathematical algorithms misc oral histopathology misc Dentistry Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis
authorStr	Abhishek Banerjee
ppnlink_with_tag_str_mv	@@773@@(DE-627)1725660016
format	electronic Article
delete_txt_mv	keep
author_role	aut aut aut aut aut
collection	DOAJ
remote_str	true
callnumber-label	RK1-715
illustrated	Not Illustrated
issn	23483172
topic_title	RK1-715 Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis Diagnostic algorithms digitization mathematical algorithms oral histopathology
topic	misc RK1-715 misc Diagnostic algorithms misc digitization misc mathematical algorithms misc oral histopathology misc Dentistry
topic_unstemmed	misc RK1-715 misc Diagnostic algorithms misc digitization misc mathematical algorithms misc oral histopathology misc Dentistry
topic_browse	misc RK1-715 misc Diagnostic algorithms misc digitization misc mathematical algorithms misc oral histopathology misc Dentistry
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	cr
hierarchy_parent_title	Journal of Dental Research and Review
hierarchy_parent_id	1725660016
hierarchy_top_title	Journal of Dental Research and Review
isfreeaccess_txt	true
familylinks_str_mv	(DE-627)1725660016
title	Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis
ctrlnum	(DE-627)DOAJ055658954 (DE-599)DOAJ303cae508c8042368b9d5eea50ae15d3
title_full	Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis
author_sort	Abhishek Banerjee
journal	Journal of Dental Research and Review
journalStr	Journal of Dental Research and Review
callnumber-first-code	R
lang_code	eng
isOA_bool	true
recordtype	marc
publishDateSort	2015
contenttype_str_mv	txt
container_start_page	97
author_browse	Abhishek Banerjee Venkatesh V Kamath R M Lavanya S K Shruthi M Deepa
container_volume	2
class	RK1-715
format_se	Elektronische Aufsätze
author-letter	Abhishek Banerjee
doi_str_mv	10.4103/2348-2915.161216
author2-role	verfasserin
title_sort	mathematical (diagnostic) algorithms in the digitization of oral histopathology: the new frontier in histopathological diagnosis
callnumber	RK1-715
title_auth	Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis
abstract	The technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms) include both object based (object features, structures) and pixel based (texture) measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms) in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis.
abstractGer	The technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms) include both object based (object features, structures) and pixel based (texture) measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms) in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis.
abstract_unstemmed	The technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms) include both object based (object features, structures) and pixel based (texture) measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms) in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis.
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700
container_issue	2
title_short	Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis
url	https://doi.org/10.4103/2348-2915.161216 https://doaj.org/article/303cae508c8042368b9d5eea50ae15d3 http://www.jdrr.org/article.asp?issn=2348-2915;year=2015;volume=2;issue=2;spage=97;epage=101;aulast=Banerjee https://doaj.org/toc/2348-2915 https://doaj.org/toc/2348-3172
remote_bool	true
author2	Venkatesh V Kamath R M Lavanya S K Shruthi M Deepa
author2Str	Venkatesh V Kamath R M Lavanya S K Shruthi M Deepa
ppnlink	1725660016
callnumber-subject	RK - Dentistry
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	false
doi_str	10.4103/2348-2915.161216
callnumber-a	RK1-715
up_date	2024-07-03T16:16:53.274Z
_version_	1803575270602440704
fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ055658954</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502090854.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2015 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.4103/2348-2915.161216</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ055658954</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ303cae508c8042368b9d5eea50ae15d3</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">RK1-715</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Abhishek Banerjee</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</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 technological progress in the digitalization of a complete histological glass slide has opened a new door in the tissue based diagnosis. Automated slide diagnosis can be made possible by the use of mathematical algorithms which are formulated by binary codes or values. These algorithms (diagnostic algorithms) include both object based (object features, structures) and pixel based (texture) measures. The intra- and inter-observer errors inherent in the visual diagnosis of a histopathological slide are largely replaced by the use of diagnostic algorithms leading to a standardized and reproducible diagnosis. The present paper reviews the advances in digital histopathology especially related to the use of mathematical algorithms (diagnostic algorithms) in the field of oral histopathology. The literature was reviewed for data relating to the use of algorithms utilized in the construction of computational software with special applications in oral histopathological diagnosis. The data were analyzed, and the types and end targets of the algorithms were tabulated. The advantages, specificities and reproducibility of the software, its shortcomings and its comparison with traditional methods of histopathological diagnosis were evaluated. Algorithms help in automated slide diagnosis by creating software with possible reduced errors and bias with a high degree of specificity, sensitivity, and reproducibility. Akin to the identification of thumbprints and faces, software for histopathological diagnosis will in the near future be an important part of the histopathological diagnosis.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Diagnostic algorithms</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">digitization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">mathematical algorithms</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">oral histopathology</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Dentistry</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Venkatesh V Kamath</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">R M Lavanya</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">S K Shruthi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">M Deepa</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">Journal of Dental Research and Review</subfield><subfield code="d">Wolters Kluwer Medknow Publications, 2017</subfield><subfield code="g">2(2015), 2, Seite 97-101</subfield><subfield code="w">(DE-627)1725660016</subfield><subfield code="x">23483172</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:2</subfield><subfield code="g">year:2015</subfield><subfield code="g">number:2</subfield><subfield code="g">pages:97-101</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.4103/2348-2915.161216</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/303cae508c8042368b9d5eea50ae15d3</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://www.jdrr.org/article.asp?issn=2348-2915;year=2015;volume=2;issue=2;spage=97;epage=101;aulast=Banerjee</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2348-2915</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/2348-3172</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">SSG-OLC-PHA</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_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</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_170</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_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_602</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_4012</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_4249</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_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_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">2</subfield><subfield code="j">2015</subfield><subfield code="e">2</subfield><subfield code="h">97-101</subfield></datafield></record></collection>
score	7.3986073

Nicht das Richtige dabei?

Schreiben Sie uns!

Mathematical (diagnostic) algorithms in the digitization of oral histopathology: The new frontier in histopathological diagnosis

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?