{"id":"https://openalex.org/W2087540011","doi":"https://doi.org/10.1142/s0218213007003448","title":"GROUND-GLASS OPACITY DETECTION BY USING CORRELATION BETWEEN SUCCESSIVE SLICE IMAGES","display_name":"GROUND-GLASS OPACITY DETECTION BY USING CORRELATION BETWEEN SUCCESSIVE SLICE IMAGES","publication_year":2007,"publication_date":"2007-08-01","ids":{"openalex":"https://openalex.org/W2087540011","doi":"https://doi.org/10.1142/s0218213007003448","mag":"2087540011"},"language":"en","primary_location":{"id":"doi:10.1142/s0218213007003448","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218213007003448","pdf_url":null,"source":{"id":"https://openalex.org/S178780388","display_name":"International Journal of Artificial Intelligence Tools","issn_l":"0218-2130","issn":["0218-2130","1793-6349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Artificial Intelligence Tools","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://kyutech.repo.nii.ac.jp/records/86","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080756118","display_name":"Hyoung Seop Kim","orcid":"https://orcid.org/0000-0002-3155-583X"},"institutions":[{"id":"https://openalex.org/I207014233","display_name":"Kyushu Institute of Technology","ror":"https://ror.org/02278tr80","country_code":"JP","type":"education","lineage":["https://openalex.org/I207014233"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"HYOUNGSEOP KIM","raw_affiliation_strings":["Department of Control Engineering, Kyushu Institute of Technology, 1-1, Kitakyushu City, Fukuoka 804-8550, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Control Engineering, Kyushu Institute of Technology, 1-1, Kitakyushu City, Fukuoka 804-8550, Japan","institution_ids":["https://openalex.org/I207014233"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070250888","display_name":"Masaki Maekado","orcid":null},"institutions":[{"id":"https://openalex.org/I207014233","display_name":"Kyushu Institute of Technology","ror":"https://ror.org/02278tr80","country_code":"JP","type":"education","lineage":["https://openalex.org/I207014233"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"MASAKI MAEKADO","raw_affiliation_strings":["Department of Control Engineering, Kyushu Institute of Technology, 1-1, Kitakyushu City, Fukuoka 804-8550, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Control Engineering, Kyushu Institute of Technology, 1-1, Kitakyushu City, Fukuoka 804-8550, Japan","institution_ids":["https://openalex.org/I207014233"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103084139","display_name":"Joo Kooi Tan","orcid":"https://orcid.org/0000-0001-9611-7139"},"institutions":[{"id":"https://openalex.org/I207014233","display_name":"Kyushu Institute of Technology","ror":"https://ror.org/02278tr80","country_code":"JP","type":"education","lineage":["https://openalex.org/I207014233"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"JOO KOOI TAN","raw_affiliation_strings":["Department of Control Engineering, Kyushu Institute of Technology, 1-1, Kitakyushu City, Fukuoka 804-8550, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Control Engineering, Kyushu Institute of Technology, 1-1, Kitakyushu City, Fukuoka 804-8550, Japan","institution_ids":["https://openalex.org/I207014233"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040103126","display_name":"Seiji Ishikawa","orcid":"https://orcid.org/0000-0002-5044-7789"},"institutions":[{"id":"https://openalex.org/I207014233","display_name":"Kyushu Institute of Technology","ror":"https://ror.org/02278tr80","country_code":"JP","type":"education","lineage":["https://openalex.org/I207014233"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"SEIJI ISHIKAWA","raw_affiliation_strings":["Department of Control Engineering, Kyushu Institute of Technology, 1-1, Kitakyushu City, Fukuoka 804-8550, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Control Engineering, Kyushu Institute of Technology, 1-1, Kitakyushu City, Fukuoka 804-8550, Japan","institution_ids":["https://openalex.org/I207014233"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111872746","display_name":"Masaaki Tsukuda","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128667","display_name":"Jiseikai Welfare Kyusyu Hospital","ror":"https://ror.org/03paakw30","country_code":"JP","type":"healthcare","lineage":["https://openalex.org/I4210128667"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"MASAAKI TSUKUDA","raw_affiliation_strings":["Kyusyu Kouseinenkin Hospital, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyusyu Kouseinenkin Hospital, Japan","institution_ids":["https://openalex.org/I4210128667"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5080756118"],"corresponding_institution_ids":["https://openalex.org/I207014233"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.12886159,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"16","issue":"04","first_page":"583","last_page":"592"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ground-glass-opacity","display_name":"Ground-glass opacity","score":0.7143117189407349},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.673015832901001},{"id":"https://openalex.org/keywords/thorax","display_name":"Thorax (insect anatomy)","score":0.6149365305900574},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5883305072784424},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5540470480918884},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.5407341718673706},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5351945161819458},{"id":"https://openalex.org/keywords/lung","display_name":"Lung","score":0.5054810047149658},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4857242703437805},{"id":"https://openalex.org/keywords/opacity","display_name":"Opacity","score":0.42890721559524536},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.41331711411476135},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4004051983356476},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3838765621185303},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.25550055503845215},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23963195085525513},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2030065655708313},{"id":"https://openalex.org/keywords/anatomy","display_name":"Anatomy","score":0.11468014121055603},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07605290412902832},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.06211888790130615}],"concepts":[{"id":"https://openalex.org/C2777001051","wikidata":"https://www.wikidata.org/wiki/Q3150728","display_name":"Ground-glass opacity","level":4,"score":0.7143117189407349},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.673015832901001},{"id":"https://openalex.org/C97834683","wikidata":"https://www.wikidata.org/wiki/Q942508","display_name":"Thorax (insect anatomy)","level":2,"score":0.6149365305900574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5883305072784424},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5540470480918884},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.5407341718673706},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5351945161819458},{"id":"https://openalex.org/C2777714996","wikidata":"https://www.wikidata.org/wiki/Q7886","display_name":"Lung","level":2,"score":0.5054810047149658},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4857242703437805},{"id":"https://openalex.org/C60056205","wikidata":"https://www.wikidata.org/wiki/Q691914","display_name":"Opacity","level":2,"score":0.42890721559524536},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.41331711411476135},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4004051983356476},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3838765621185303},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.25550055503845215},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23963195085525513},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2030065655708313},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.11468014121055603},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07605290412902832},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.06211888790130615},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C2781182431","wikidata":"https://www.wikidata.org/wiki/Q356033","display_name":"Adenocarcinoma","level":3,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1142/s0218213007003448","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218213007003448","pdf_url":null,"source":{"id":"https://openalex.org/S178780388","display_name":"International Journal of Artificial Intelligence Tools","issn_l":"0218-2130","issn":["0218-2130","1793-6349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Artificial Intelligence Tools","raw_type":"journal-article"},{"id":"pmh:oai:irdb.nii.ac.jp:01216:0000923898","is_oa":true,"landing_page_url":"https://kyutech.repo.nii.ac.jp/records/86","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"International Journal on Artificial Intelligence Tools","raw_type":"journal article"},{"id":"pmh:oai:kyutech.repo.nii.ac.jp:00000086","is_oa":true,"landing_page_url":"http://hdl.handle.net/10228/330","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"AM"}],"best_oa_location":{"id":"pmh:oai:irdb.nii.ac.jp:01216:0000923898","is_oa":true,"landing_page_url":"https://kyutech.repo.nii.ac.jp/records/86","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"International Journal on Artificial Intelligence Tools","raw_type":"journal article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1977209481","https://openalex.org/W2017898137","https://openalex.org/W2032314996","https://openalex.org/W2044140763","https://openalex.org/W2047621404","https://openalex.org/W2071131529","https://openalex.org/W2104197853","https://openalex.org/W2120085308","https://openalex.org/W2120597332","https://openalex.org/W2153810084","https://openalex.org/W2201161230"],"related_works":["https://openalex.org/W2161791806","https://openalex.org/W4366824690","https://openalex.org/W2073474947","https://openalex.org/W2613656770","https://openalex.org/W2482431380","https://openalex.org/W2053059436","https://openalex.org/W4313201885","https://openalex.org/W2082077321","https://openalex.org/W2903403101","https://openalex.org/W1484681647"],"abstract_inverted_index":{"Medical":[0],"imaging":[1,9],"systems":[2],"such":[3,42],"as":[4,43,145],"computed":[5],"tomography,":[6],"magnetic":[7],"resonance":[8],"provided":[10],"a":[11,59,80,104,199],"high":[12],"resolution":[13],"image":[14,27,54,184],"for":[15,83,92,119],"powerful":[16],"diagnostic":[17],"tool":[18],"in":[19],"visual":[20],"inspection":[21],"fields":[22],"by":[23,100,156],"physician.":[24],"Especially":[25],"MDCT":[26],"can":[28],"be":[29],"used":[30],"to":[31,162,171],"obtain":[32],"detailed":[33],"images":[34],"of":[35,86,106,121,124,188],"the":[36,44,47,52,96,107,116,122,132,140,146,151,160,165,172],"pulmonary":[37,40,45,48],"anatomy,":[38],"including":[39],"diseases":[41],"nodules,":[46],"vein,":[49],"etc.":[50],"In":[51,111],"medical":[53],"processing":[55],"technique,":[56],"segmentation":[57,85],"is":[58,143,154,177],"difficult":[60],"task":[61],"because":[62],"surrounding":[63],"soft":[64],"tissues":[65],"and":[66,72,89,128,186],"organs":[67],"have":[68],"similar":[69],"CT":[70,109,174,183],"values":[71],"sometimes":[73],"contact":[74],"with":[75,169,198],"each":[76,134],"other.":[77],"We":[78],"propose":[79],"new":[81],"technique":[82],"automatic":[84],"lung":[87,98,117,148,167],"regions":[88,99],"its":[90],"classification":[91],"ground-glass":[93,152],"opacity":[94,153],"from":[95,131,164],"extracted":[97,166],"computer":[101],"based":[102],"on":[103,159],"set":[105],"thorax":[108,173,182],"images.":[110,136,175],"this":[112],"paper,":[113],"we":[114],"segment":[115],"region":[118,123,138,168],"extraction":[120],"interest":[125],"employing":[126,179],"binarization":[127],"labeling":[129],"process":[130],"inputted":[133],"slices":[135],"The":[137],"having":[139],"largest":[141],"area":[142],"regarded":[144],"tentative":[147],"regions.":[149],"Furthermore,":[150],"classified":[155],"correlation":[157],"distribution":[158],"slice":[161,163],"respect":[170],"Experiment":[176],"performed":[178],"twenty":[180],"six":[181],"sets":[185],"96%":[187],"recognition":[189],"rates":[190],"were":[191],"achieved.":[192],"Obtained":[193],"results":[194],"are":[195],"shown":[196],"along":[197],"discussion.":[200]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
