Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data
Abstract We developed a novel three-dimensional (3D) image simulation system, focused on pulmonary segmentectomy. The novel algorithms run by the software, which are independent of the differences in computed tomography (CT) values of vascular structures, enabled the creation of 3D images from unenh...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Nakao, Masayuki [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2021 |
|---|
| Schlagwörter: |
|---|
| Anmerkung: |
© The Japanese Association for Thoracic Surgery 2021 |
|---|
| Übergeordnetes Werk: |
Enthalten in: The Japanese journal of thoracic and cardiovascular surgery - Tōkyō : Springer Japan, 1998, 70(2021), 3 vom: 23. Nov., Seite 312-314 |
|---|---|
| Übergeordnetes Werk: |
volume:70 ; year:2021 ; number:3 ; day:23 ; month:11 ; pages:312-314 |
| Links: |
|---|
| DOI / URN: |
10.1007/s11748-021-01750-x |
|---|
| Katalog-ID: |
SPR04634537X |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | SPR04634537X | ||
| 003 | DE-627 | ||
| 005 | 20230507115408.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 220226s2021 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s11748-021-01750-x |2 doi | |
| 035 | |a (DE-627)SPR04634537X | ||
| 035 | |a (SPR)s11748-021-01750-x-e | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Nakao, Masayuki |e verfasserin |0 (orcid)0000-0003-2913-6836 |4 aut | |
| 245 | 1 | 0 | |a Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data |
| 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 | ||
| 500 | |a © The Japanese Association for Thoracic Surgery 2021 | ||
| 520 | |a Abstract We developed a novel three-dimensional (3D) image simulation system, focused on pulmonary segmentectomy. The novel algorithms run by the software, which are independent of the differences in computed tomography (CT) values of vascular structures, enabled the creation of 3D images from unenhanced CT data with accuracy comparable to that from contrast-enhanced CT data. To evaluate the anatomical accuracy, we compared it between images created from unenhanced and contrast-enhanced CT in seven patients who underwent thoracoscopic segmentectomy. With regard to the automatic recognition of pulmonary vessels, the 3D image from unenhanced CT falsely recognized one or two points in two cases, whereas that from contrast-enhanced CT false recognitions in one case. Both 3D images had similar creation time and capability for identifying the intersegmental plain. The novel 3D image simulation for segmentectomy from unenhanced CT had sufficient anatomical accuracy for practical use but required attention due to inevitable minor false recognition. | ||
| 650 | 4 | |a Unenhanced computed tomography |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Segmentectomy |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Simulation |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Omura, Kenshiro |4 aut | |
| 700 | 1 | |a Hashimoto, Kohei |4 aut | |
| 700 | 1 | |a Ichinose, Junji |4 aut | |
| 700 | 1 | |a Matsuura, Yosuke |4 aut | |
| 700 | 1 | |a Okumura, Sakae |4 aut | |
| 700 | 1 | |a Mun, Mingyon |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t The Japanese journal of thoracic and cardiovascular surgery |d Tōkyō : Springer Japan, 1998 |g 70(2021), 3 vom: 23. Nov., Seite 312-314 |w (DE-627)539545104 |w (DE-600)2381600-4 |x 1863-2092 |7 nnns |
| 773 | 1 | 8 | |g volume:70 |g year:2021 |g number:3 |g day:23 |g month:11 |g pages:312-314 |
| 856 | 4 | 0 | |u https://dx.doi.org/10.1007/s11748-021-01750-x |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_SPRINGER | ||
| 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_65 | ||
| 912 | |a GBV_ILN_69 | ||
| 912 | |a GBV_ILN_70 | ||
| 912 | |a GBV_ILN_73 | ||
| 912 | |a GBV_ILN_74 | ||
| 912 | |a GBV_ILN_90 | ||
| 912 | |a GBV_ILN_95 | ||
| 912 | |a GBV_ILN_100 | ||
| 912 | |a GBV_ILN_105 | ||
| 912 | |a GBV_ILN_120 | ||
| 912 | |a GBV_ILN_152 | ||
| 912 | |a GBV_ILN_161 | ||
| 912 | |a GBV_ILN_171 | ||
| 912 | |a GBV_ILN_187 | ||
| 912 | |a GBV_ILN_224 | ||
| 912 | |a GBV_ILN_250 | ||
| 912 | |a GBV_ILN_281 | ||
| 912 | |a GBV_ILN_285 | ||
| 912 | |a GBV_ILN_293 | ||
| 912 | |a GBV_ILN_370 | ||
| 912 | |a GBV_ILN_602 | ||
| 912 | |a GBV_ILN_702 | ||
| 951 | |a AR | ||
| 952 | |d 70 |j 2021 |e 3 |b 23 |c 11 |h 312-314 | ||
| author_variant |
m n mn k o ko k h kh j i ji y m ym s o so m m mm |
|---|---|
| matchkey_str |
article:18632092:2021----::hedmninlmgsmltofrugemnetmfouehn |
| hierarchy_sort_str |
2021 |
| publishDate |
2021 |
| allfields |
10.1007/s11748-021-01750-x doi (DE-627)SPR04634537X (SPR)s11748-021-01750-x-e DE-627 ger DE-627 rakwb eng Nakao, Masayuki verfasserin (orcid)0000-0003-2913-6836 aut Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Japanese Association for Thoracic Surgery 2021 Abstract We developed a novel three-dimensional (3D) image simulation system, focused on pulmonary segmentectomy. The novel algorithms run by the software, which are independent of the differences in computed tomography (CT) values of vascular structures, enabled the creation of 3D images from unenhanced CT data with accuracy comparable to that from contrast-enhanced CT data. To evaluate the anatomical accuracy, we compared it between images created from unenhanced and contrast-enhanced CT in seven patients who underwent thoracoscopic segmentectomy. With regard to the automatic recognition of pulmonary vessels, the 3D image from unenhanced CT falsely recognized one or two points in two cases, whereas that from contrast-enhanced CT false recognitions in one case. Both 3D images had similar creation time and capability for identifying the intersegmental plain. The novel 3D image simulation for segmentectomy from unenhanced CT had sufficient anatomical accuracy for practical use but required attention due to inevitable minor false recognition. Unenhanced computed tomography (dpeaa)DE-He213 Segmentectomy (dpeaa)DE-He213 Simulation (dpeaa)DE-He213 Omura, Kenshiro aut Hashimoto, Kohei aut Ichinose, Junji aut Matsuura, Yosuke aut Okumura, Sakae aut Mun, Mingyon aut Enthalten in The Japanese journal of thoracic and cardiovascular surgery Tōkyō : Springer Japan, 1998 70(2021), 3 vom: 23. Nov., Seite 312-314 (DE-627)539545104 (DE-600)2381600-4 1863-2092 nnns volume:70 year:2021 number:3 day:23 month:11 pages:312-314 https://dx.doi.org/10.1007/s11748-021-01750-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 70 2021 3 23 11 312-314 |
| spelling |
10.1007/s11748-021-01750-x doi (DE-627)SPR04634537X (SPR)s11748-021-01750-x-e DE-627 ger DE-627 rakwb eng Nakao, Masayuki verfasserin (orcid)0000-0003-2913-6836 aut Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Japanese Association for Thoracic Surgery 2021 Abstract We developed a novel three-dimensional (3D) image simulation system, focused on pulmonary segmentectomy. The novel algorithms run by the software, which are independent of the differences in computed tomography (CT) values of vascular structures, enabled the creation of 3D images from unenhanced CT data with accuracy comparable to that from contrast-enhanced CT data. To evaluate the anatomical accuracy, we compared it between images created from unenhanced and contrast-enhanced CT in seven patients who underwent thoracoscopic segmentectomy. With regard to the automatic recognition of pulmonary vessels, the 3D image from unenhanced CT falsely recognized one or two points in two cases, whereas that from contrast-enhanced CT false recognitions in one case. Both 3D images had similar creation time and capability for identifying the intersegmental plain. The novel 3D image simulation for segmentectomy from unenhanced CT had sufficient anatomical accuracy for practical use but required attention due to inevitable minor false recognition. Unenhanced computed tomography (dpeaa)DE-He213 Segmentectomy (dpeaa)DE-He213 Simulation (dpeaa)DE-He213 Omura, Kenshiro aut Hashimoto, Kohei aut Ichinose, Junji aut Matsuura, Yosuke aut Okumura, Sakae aut Mun, Mingyon aut Enthalten in The Japanese journal of thoracic and cardiovascular surgery Tōkyō : Springer Japan, 1998 70(2021), 3 vom: 23. Nov., Seite 312-314 (DE-627)539545104 (DE-600)2381600-4 1863-2092 nnns volume:70 year:2021 number:3 day:23 month:11 pages:312-314 https://dx.doi.org/10.1007/s11748-021-01750-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 70 2021 3 23 11 312-314 |
| allfields_unstemmed |
10.1007/s11748-021-01750-x doi (DE-627)SPR04634537X (SPR)s11748-021-01750-x-e DE-627 ger DE-627 rakwb eng Nakao, Masayuki verfasserin (orcid)0000-0003-2913-6836 aut Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Japanese Association for Thoracic Surgery 2021 Abstract We developed a novel three-dimensional (3D) image simulation system, focused on pulmonary segmentectomy. The novel algorithms run by the software, which are independent of the differences in computed tomography (CT) values of vascular structures, enabled the creation of 3D images from unenhanced CT data with accuracy comparable to that from contrast-enhanced CT data. To evaluate the anatomical accuracy, we compared it between images created from unenhanced and contrast-enhanced CT in seven patients who underwent thoracoscopic segmentectomy. With regard to the automatic recognition of pulmonary vessels, the 3D image from unenhanced CT falsely recognized one or two points in two cases, whereas that from contrast-enhanced CT false recognitions in one case. Both 3D images had similar creation time and capability for identifying the intersegmental plain. The novel 3D image simulation for segmentectomy from unenhanced CT had sufficient anatomical accuracy for practical use but required attention due to inevitable minor false recognition. Unenhanced computed tomography (dpeaa)DE-He213 Segmentectomy (dpeaa)DE-He213 Simulation (dpeaa)DE-He213 Omura, Kenshiro aut Hashimoto, Kohei aut Ichinose, Junji aut Matsuura, Yosuke aut Okumura, Sakae aut Mun, Mingyon aut Enthalten in The Japanese journal of thoracic and cardiovascular surgery Tōkyō : Springer Japan, 1998 70(2021), 3 vom: 23. Nov., Seite 312-314 (DE-627)539545104 (DE-600)2381600-4 1863-2092 nnns volume:70 year:2021 number:3 day:23 month:11 pages:312-314 https://dx.doi.org/10.1007/s11748-021-01750-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 70 2021 3 23 11 312-314 |
| allfieldsGer |
10.1007/s11748-021-01750-x doi (DE-627)SPR04634537X (SPR)s11748-021-01750-x-e DE-627 ger DE-627 rakwb eng Nakao, Masayuki verfasserin (orcid)0000-0003-2913-6836 aut Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Japanese Association for Thoracic Surgery 2021 Abstract We developed a novel three-dimensional (3D) image simulation system, focused on pulmonary segmentectomy. The novel algorithms run by the software, which are independent of the differences in computed tomography (CT) values of vascular structures, enabled the creation of 3D images from unenhanced CT data with accuracy comparable to that from contrast-enhanced CT data. To evaluate the anatomical accuracy, we compared it between images created from unenhanced and contrast-enhanced CT in seven patients who underwent thoracoscopic segmentectomy. With regard to the automatic recognition of pulmonary vessels, the 3D image from unenhanced CT falsely recognized one or two points in two cases, whereas that from contrast-enhanced CT false recognitions in one case. Both 3D images had similar creation time and capability for identifying the intersegmental plain. The novel 3D image simulation for segmentectomy from unenhanced CT had sufficient anatomical accuracy for practical use but required attention due to inevitable minor false recognition. Unenhanced computed tomography (dpeaa)DE-He213 Segmentectomy (dpeaa)DE-He213 Simulation (dpeaa)DE-He213 Omura, Kenshiro aut Hashimoto, Kohei aut Ichinose, Junji aut Matsuura, Yosuke aut Okumura, Sakae aut Mun, Mingyon aut Enthalten in The Japanese journal of thoracic and cardiovascular surgery Tōkyō : Springer Japan, 1998 70(2021), 3 vom: 23. Nov., Seite 312-314 (DE-627)539545104 (DE-600)2381600-4 1863-2092 nnns volume:70 year:2021 number:3 day:23 month:11 pages:312-314 https://dx.doi.org/10.1007/s11748-021-01750-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 70 2021 3 23 11 312-314 |
| allfieldsSound |
10.1007/s11748-021-01750-x doi (DE-627)SPR04634537X (SPR)s11748-021-01750-x-e DE-627 ger DE-627 rakwb eng Nakao, Masayuki verfasserin (orcid)0000-0003-2913-6836 aut Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Japanese Association for Thoracic Surgery 2021 Abstract We developed a novel three-dimensional (3D) image simulation system, focused on pulmonary segmentectomy. The novel algorithms run by the software, which are independent of the differences in computed tomography (CT) values of vascular structures, enabled the creation of 3D images from unenhanced CT data with accuracy comparable to that from contrast-enhanced CT data. To evaluate the anatomical accuracy, we compared it between images created from unenhanced and contrast-enhanced CT in seven patients who underwent thoracoscopic segmentectomy. With regard to the automatic recognition of pulmonary vessels, the 3D image from unenhanced CT falsely recognized one or two points in two cases, whereas that from contrast-enhanced CT false recognitions in one case. Both 3D images had similar creation time and capability for identifying the intersegmental plain. The novel 3D image simulation for segmentectomy from unenhanced CT had sufficient anatomical accuracy for practical use but required attention due to inevitable minor false recognition. Unenhanced computed tomography (dpeaa)DE-He213 Segmentectomy (dpeaa)DE-He213 Simulation (dpeaa)DE-He213 Omura, Kenshiro aut Hashimoto, Kohei aut Ichinose, Junji aut Matsuura, Yosuke aut Okumura, Sakae aut Mun, Mingyon aut Enthalten in The Japanese journal of thoracic and cardiovascular surgery Tōkyō : Springer Japan, 1998 70(2021), 3 vom: 23. Nov., Seite 312-314 (DE-627)539545104 (DE-600)2381600-4 1863-2092 nnns volume:70 year:2021 number:3 day:23 month:11 pages:312-314 https://dx.doi.org/10.1007/s11748-021-01750-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 AR 70 2021 3 23 11 312-314 |
| language |
English |
| source |
Enthalten in The Japanese journal of thoracic and cardiovascular surgery 70(2021), 3 vom: 23. Nov., Seite 312-314 volume:70 year:2021 number:3 day:23 month:11 pages:312-314 |
| sourceStr |
Enthalten in The Japanese journal of thoracic and cardiovascular surgery 70(2021), 3 vom: 23. Nov., Seite 312-314 volume:70 year:2021 number:3 day:23 month:11 pages:312-314 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Unenhanced computed tomography Segmentectomy Simulation |
| isfreeaccess_bool |
false |
| container_title |
The Japanese journal of thoracic and cardiovascular surgery |
| authorswithroles_txt_mv |
Nakao, Masayuki @@aut@@ Omura, Kenshiro @@aut@@ Hashimoto, Kohei @@aut@@ Ichinose, Junji @@aut@@ Matsuura, Yosuke @@aut@@ Okumura, Sakae @@aut@@ Mun, Mingyon @@aut@@ |
| publishDateDaySort_date |
2021-11-23T00:00:00Z |
| hierarchy_top_id |
539545104 |
| id |
SPR04634537X |
| 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">SPR04634537X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230507115408.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">220226s2021 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11748-021-01750-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR04634537X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11748-021-01750-x-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Nakao, Masayuki</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0003-2913-6836</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data</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="500" ind1=" " ind2=" "><subfield code="a">© The Japanese Association for Thoracic Surgery 2021</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract We developed a novel three-dimensional (3D) image simulation system, focused on pulmonary segmentectomy. The novel algorithms run by the software, which are independent of the differences in computed tomography (CT) values of vascular structures, enabled the creation of 3D images from unenhanced CT data with accuracy comparable to that from contrast-enhanced CT data. To evaluate the anatomical accuracy, we compared it between images created from unenhanced and contrast-enhanced CT in seven patients who underwent thoracoscopic segmentectomy. With regard to the automatic recognition of pulmonary vessels, the 3D image from unenhanced CT falsely recognized one or two points in two cases, whereas that from contrast-enhanced CT false recognitions in one case. Both 3D images had similar creation time and capability for identifying the intersegmental plain. The novel 3D image simulation for segmentectomy from unenhanced CT had sufficient anatomical accuracy for practical use but required attention due to inevitable minor false recognition.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Unenhanced computed tomography</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Segmentectomy</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Simulation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Omura, Kenshiro</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hashimoto, Kohei</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ichinose, Junji</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Matsuura, Yosuke</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Okumura, Sakae</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mun, Mingyon</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">The Japanese journal of thoracic and cardiovascular surgery</subfield><subfield code="d">Tōkyō : Springer Japan, 1998</subfield><subfield code="g">70(2021), 3 vom: 23. Nov., Seite 312-314</subfield><subfield code="w">(DE-627)539545104</subfield><subfield code="w">(DE-600)2381600-4</subfield><subfield code="x">1863-2092</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:70</subfield><subfield code="g">year:2021</subfield><subfield code="g">number:3</subfield><subfield code="g">day:23</subfield><subfield code="g">month:11</subfield><subfield code="g">pages:312-314</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s11748-021-01750-x</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" 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_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_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</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_100</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_120</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_152</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_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_187</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_250</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_281</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_702</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">70</subfield><subfield code="j">2021</subfield><subfield code="e">3</subfield><subfield code="b">23</subfield><subfield code="c">11</subfield><subfield code="h">312-314</subfield></datafield></record></collection>
|
| author |
Nakao, Masayuki |
| spellingShingle |
Nakao, Masayuki misc Unenhanced computed tomography misc Segmentectomy misc Simulation Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data |
| authorStr |
Nakao, Masayuki |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)539545104 |
| format |
electronic Article |
| delete_txt_mv |
keep |
| author_role |
aut aut aut aut aut aut aut |
| collection |
springer |
| remote_str |
true |
| illustrated |
Not Illustrated |
| issn |
1863-2092 |
| topic_title |
Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data Unenhanced computed tomography (dpeaa)DE-He213 Segmentectomy (dpeaa)DE-He213 Simulation (dpeaa)DE-He213 |
| topic |
misc Unenhanced computed tomography misc Segmentectomy misc Simulation |
| topic_unstemmed |
misc Unenhanced computed tomography misc Segmentectomy misc Simulation |
| topic_browse |
misc Unenhanced computed tomography misc Segmentectomy misc Simulation |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
cr |
| hierarchy_parent_title |
The Japanese journal of thoracic and cardiovascular surgery |
| hierarchy_parent_id |
539545104 |
| hierarchy_top_title |
The Japanese journal of thoracic and cardiovascular surgery |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)539545104 (DE-600)2381600-4 |
| title |
Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data |
| ctrlnum |
(DE-627)SPR04634537X (SPR)s11748-021-01750-x-e |
| title_full |
Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data |
| author_sort |
Nakao, Masayuki |
| journal |
The Japanese journal of thoracic and cardiovascular surgery |
| journalStr |
The Japanese journal of thoracic and cardiovascular surgery |
| lang_code |
eng |
| isOA_bool |
false |
| recordtype |
marc |
| publishDateSort |
2021 |
| contenttype_str_mv |
txt |
| container_start_page |
312 |
| author_browse |
Nakao, Masayuki Omura, Kenshiro Hashimoto, Kohei Ichinose, Junji Matsuura, Yosuke Okumura, Sakae Mun, Mingyon |
| container_volume |
70 |
| format_se |
Elektronische Aufsätze |
| author-letter |
Nakao, Masayuki |
| doi_str_mv |
10.1007/s11748-021-01750-x |
| normlink |
(ORCID)0000-0003-2913-6836 |
| normlink_prefix_str_mv |
(orcid)0000-0003-2913-6836 |
| title_sort |
three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data |
| title_auth |
Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data |
| abstract |
Abstract We developed a novel three-dimensional (3D) image simulation system, focused on pulmonary segmentectomy. The novel algorithms run by the software, which are independent of the differences in computed tomography (CT) values of vascular structures, enabled the creation of 3D images from unenhanced CT data with accuracy comparable to that from contrast-enhanced CT data. To evaluate the anatomical accuracy, we compared it between images created from unenhanced and contrast-enhanced CT in seven patients who underwent thoracoscopic segmentectomy. With regard to the automatic recognition of pulmonary vessels, the 3D image from unenhanced CT falsely recognized one or two points in two cases, whereas that from contrast-enhanced CT false recognitions in one case. Both 3D images had similar creation time and capability for identifying the intersegmental plain. The novel 3D image simulation for segmentectomy from unenhanced CT had sufficient anatomical accuracy for practical use but required attention due to inevitable minor false recognition. © The Japanese Association for Thoracic Surgery 2021 |
| abstractGer |
Abstract We developed a novel three-dimensional (3D) image simulation system, focused on pulmonary segmentectomy. The novel algorithms run by the software, which are independent of the differences in computed tomography (CT) values of vascular structures, enabled the creation of 3D images from unenhanced CT data with accuracy comparable to that from contrast-enhanced CT data. To evaluate the anatomical accuracy, we compared it between images created from unenhanced and contrast-enhanced CT in seven patients who underwent thoracoscopic segmentectomy. With regard to the automatic recognition of pulmonary vessels, the 3D image from unenhanced CT falsely recognized one or two points in two cases, whereas that from contrast-enhanced CT false recognitions in one case. Both 3D images had similar creation time and capability for identifying the intersegmental plain. The novel 3D image simulation for segmentectomy from unenhanced CT had sufficient anatomical accuracy for practical use but required attention due to inevitable minor false recognition. © The Japanese Association for Thoracic Surgery 2021 |
| abstract_unstemmed |
Abstract We developed a novel three-dimensional (3D) image simulation system, focused on pulmonary segmentectomy. The novel algorithms run by the software, which are independent of the differences in computed tomography (CT) values of vascular structures, enabled the creation of 3D images from unenhanced CT data with accuracy comparable to that from contrast-enhanced CT data. To evaluate the anatomical accuracy, we compared it between images created from unenhanced and contrast-enhanced CT in seven patients who underwent thoracoscopic segmentectomy. With regard to the automatic recognition of pulmonary vessels, the 3D image from unenhanced CT falsely recognized one or two points in two cases, whereas that from contrast-enhanced CT false recognitions in one case. Both 3D images had similar creation time and capability for identifying the intersegmental plain. The novel 3D image simulation for segmentectomy from unenhanced CT had sufficient anatomical accuracy for practical use but required attention due to inevitable minor false recognition. © The Japanese Association for Thoracic Surgery 2021 |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER 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_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_120 GBV_ILN_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 |
| container_issue |
3 |
| title_short |
Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data |
| url |
https://dx.doi.org/10.1007/s11748-021-01750-x |
| remote_bool |
true |
| author2 |
Omura, Kenshiro Hashimoto, Kohei Ichinose, Junji Matsuura, Yosuke Okumura, Sakae Mun, Mingyon |
| author2Str |
Omura, Kenshiro Hashimoto, Kohei Ichinose, Junji Matsuura, Yosuke Okumura, Sakae Mun, Mingyon |
| ppnlink |
539545104 |
| mediatype_str_mv |
c |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1007/s11748-021-01750-x |
| up_date |
2024-07-03T21:57:59.721Z |
| _version_ |
1803596731224424448 |
| 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">SPR04634537X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230507115408.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">220226s2021 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11748-021-01750-x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR04634537X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11748-021-01750-x-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Nakao, Masayuki</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0003-2913-6836</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Three-dimensional image simulation for lung segmentectomy from unenhanced computed tomography data</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="500" ind1=" " ind2=" "><subfield code="a">© The Japanese Association for Thoracic Surgery 2021</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract We developed a novel three-dimensional (3D) image simulation system, focused on pulmonary segmentectomy. The novel algorithms run by the software, which are independent of the differences in computed tomography (CT) values of vascular structures, enabled the creation of 3D images from unenhanced CT data with accuracy comparable to that from contrast-enhanced CT data. To evaluate the anatomical accuracy, we compared it between images created from unenhanced and contrast-enhanced CT in seven patients who underwent thoracoscopic segmentectomy. With regard to the automatic recognition of pulmonary vessels, the 3D image from unenhanced CT falsely recognized one or two points in two cases, whereas that from contrast-enhanced CT false recognitions in one case. Both 3D images had similar creation time and capability for identifying the intersegmental plain. The novel 3D image simulation for segmentectomy from unenhanced CT had sufficient anatomical accuracy for practical use but required attention due to inevitable minor false recognition.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Unenhanced computed tomography</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Segmentectomy</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Simulation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Omura, Kenshiro</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hashimoto, Kohei</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ichinose, Junji</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Matsuura, Yosuke</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Okumura, Sakae</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mun, Mingyon</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">The Japanese journal of thoracic and cardiovascular surgery</subfield><subfield code="d">Tōkyō : Springer Japan, 1998</subfield><subfield code="g">70(2021), 3 vom: 23. Nov., Seite 312-314</subfield><subfield code="w">(DE-627)539545104</subfield><subfield code="w">(DE-600)2381600-4</subfield><subfield code="x">1863-2092</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:70</subfield><subfield code="g">year:2021</subfield><subfield code="g">number:3</subfield><subfield code="g">day:23</subfield><subfield code="g">month:11</subfield><subfield code="g">pages:312-314</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s11748-021-01750-x</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" 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_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_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_90</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_100</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_120</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_152</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_171</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_187</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_250</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_281</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_702</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">70</subfield><subfield code="j">2021</subfield><subfield code="e">3</subfield><subfield code="b">23</subfield><subfield code="c">11</subfield><subfield code="h">312-314</subfield></datafield></record></collection>
|
| score |
7.3996277 |