{"id":"https://openalex.org/W2807121762","doi":"https://doi.org/10.1109/isbi.2018.8363515","title":"Fully-convolutional deep-learning based system for coronary calcium score prediction from non-contrast chest CT","display_name":"Fully-convolutional deep-learning based system for coronary calcium score prediction from non-contrast chest CT","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2807121762","doi":"https://doi.org/10.1109/isbi.2018.8363515","mag":"2807121762"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2018.8363515","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054546014","display_name":"Ran Shadmi","orcid":"https://orcid.org/0000-0001-5925-0176"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ran Shadmi","raw_affiliation_strings":["Zebra Medical Vision, Shefayim, Israel"],"affiliations":[{"raw_affiliation_string":"Zebra Medical Vision, Shefayim, Israel","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048361202","display_name":"Victoria Mazo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Victoria Mazo","raw_affiliation_strings":["Zebra Medical Vision, Shefayim, Israel"],"affiliations":[{"raw_affiliation_string":"Zebra Medical Vision, Shefayim, Israel","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109468900","display_name":"Orna Bregman-Amitai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Orna Bregman-Amitai","raw_affiliation_strings":["Zebra Medical Vision, Shefayim, Israel"],"affiliations":[{"raw_affiliation_string":"Zebra Medical Vision, Shefayim, Israel","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061730992","display_name":"Eldad Elnekave","orcid":"https://orcid.org/0000-0002-3197-7338"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eldad Elnekave","raw_affiliation_strings":["Zebra Medical Vision, Shefayim, Israel"],"affiliations":[{"raw_affiliation_string":"Zebra Medical Vision, Shefayim, Israel","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054546014"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.9306,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":{"value":0.96903984,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"24","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9765999913215637,"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/agatston-score","display_name":"Agatston score","score":0.764159083366394},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.6603520512580872},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5986600518226624},{"id":"https://openalex.org/keywords/coronary-calcium-score","display_name":"Coronary Calcium Score","score":0.5666242241859436},{"id":"https://openalex.org/keywords/national-lung-screening-trial","display_name":"National Lung Screening Trial","score":0.4845673143863678},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.4753684401512146},{"id":"https://openalex.org/keywords/framingham-risk-score","display_name":"Framingham Risk Score","score":0.4601370394229889},{"id":"https://openalex.org/keywords/coronary-arteries","display_name":"Coronary arteries","score":0.4436522126197815},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4374780058860779},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.4217385947704315},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.4123036861419678},{"id":"https://openalex.org/keywords/coronary-artery-disease","display_name":"Coronary artery disease","score":0.38425126671791077},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3750544488430023},{"id":"https://openalex.org/keywords/coronary-artery-calcium","display_name":"Coronary artery calcium","score":0.3360750079154968},{"id":"https://openalex.org/keywords/lung","display_name":"Lung","score":0.3215070366859436},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2585899233818054},{"id":"https://openalex.org/keywords/lung-cancer-screening","display_name":"Lung cancer screening","score":0.22231075167655945},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.15984678268432617},{"id":"https://openalex.org/keywords/artery","display_name":"Artery","score":0.15875297784805298},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12127956748008728}],"concepts":[{"id":"https://openalex.org/C2780609585","wikidata":"https://www.wikidata.org/wiki/Q5629407","display_name":"Agatston score","level":4,"score":0.764159083366394},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.6603520512580872},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5986600518226624},{"id":"https://openalex.org/C2909917808","wikidata":"https://www.wikidata.org/wiki/Q5629407","display_name":"Coronary Calcium Score","level":4,"score":0.5666242241859436},{"id":"https://openalex.org/C2778321237","wikidata":"https://www.wikidata.org/wiki/Q17125886","display_name":"National Lung Screening Trial","level":4,"score":0.4845673143863678},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.4753684401512146},{"id":"https://openalex.org/C11783203","wikidata":"https://www.wikidata.org/wiki/Q5478027","display_name":"Framingham Risk Score","level":3,"score":0.4601370394229889},{"id":"https://openalex.org/C2778742706","wikidata":"https://www.wikidata.org/wiki/Q18361829","display_name":"Coronary arteries","level":3,"score":0.4436522126197815},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4374780058860779},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.4217385947704315},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.4123036861419678},{"id":"https://openalex.org/C2778213512","wikidata":"https://www.wikidata.org/wiki/Q844935","display_name":"Coronary artery disease","level":2,"score":0.38425126671791077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3750544488430023},{"id":"https://openalex.org/C2994533308","wikidata":"https://www.wikidata.org/wiki/Q5629407","display_name":"Coronary artery calcium","level":3,"score":0.3360750079154968},{"id":"https://openalex.org/C2777714996","wikidata":"https://www.wikidata.org/wiki/Q7886","display_name":"Lung","level":2,"score":0.3215070366859436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2585899233818054},{"id":"https://openalex.org/C2777405583","wikidata":"https://www.wikidata.org/wiki/Q6704277","display_name":"Lung cancer screening","level":3,"score":0.22231075167655945},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.15984678268432617},{"id":"https://openalex.org/C2776820930","wikidata":"https://www.wikidata.org/wiki/Q9655","display_name":"Artery","level":2,"score":0.15875297784805298},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12127956748008728},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2018.8363515","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.5799999833106995,"display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W87689928","https://openalex.org/W130099911","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1969678022","https://openalex.org/W2080825898","https://openalex.org/W2107453079","https://openalex.org/W2153785016","https://openalex.org/W2167510172","https://openalex.org/W2172289547","https://openalex.org/W2303853551","https://openalex.org/W2340907062","https://openalex.org/W2559597482","https://openalex.org/W2609077090","https://openalex.org/W2963446712","https://openalex.org/W3105894466","https://openalex.org/W4295245474","https://openalex.org/W6639824700","https://openalex.org/W6684372118","https://openalex.org/W6697648365","https://openalex.org/W6786373938"],"related_works":["https://openalex.org/W4388143145","https://openalex.org/W2202285033","https://openalex.org/W2050140713","https://openalex.org/W1994025753","https://openalex.org/W2463152536","https://openalex.org/W3102742661","https://openalex.org/W2900670601","https://openalex.org/W1991337537","https://openalex.org/W3215544397","https://openalex.org/W3211668745"],"abstract_inverted_index":{"The":[0,91],"amount":[1],"of":[2,13,40,95,103,123,130,135,137,173],"calcium":[3,17,31,65],"deposits":[4],"in":[5,47,89],"the":[6,48,164,174],"coronary":[7,64],"arteries":[8],"is":[9,32,93],"an":[10,23,53,78],"important":[11],"biomarker":[12],"cardiovascular":[14],"disease.":[15],"Coronary":[16,30],"has":[18],"traditionally":[19],"been":[20],"quantified":[21,34],"as":[22],"Agatston":[24,68,147],"score":[25,69],"using":[26],"ECG-synchronized":[27],"cardiac":[28],"CT.":[29,74],"rarely":[33],"from":[35,70,163],"general":[36],"chest":[37,73],"CT":[38],"scans,":[39],"which":[41],"nearly":[42],"10":[43],"Million":[44],"are":[45,144],"performed":[46],"US":[49],"annually.":[50],"We":[51,75,151,170],"present":[52],"automatic":[54],"method":[55,155],"based":[56],"on":[57,156],"fully-convolutional":[58],"deep":[59],"neural":[60],"network":[61],"to":[62,112],"segment":[63],"and":[66,99,108],"predict":[67],"any":[71],"non-contrast":[72],"experimented":[76],"with":[77,84,132,177],"internal":[79],"dataset":[80,92],"acquired":[81],"through":[82],"partnership":[83],"a":[85,101,119,128,157],"large":[86,159],"health":[87],"organization":[88],"Israel.":[90],"composed":[94],"1054":[96],"Chest":[97],"CTs":[98],"reflects":[100],"variety":[102],"originating":[104],"institutions,":[105],"acquisition":[106],"devices":[107],"manufacturers.":[109],"In":[110],"comparison":[111],"expert":[113],"manual":[114],"annotations,":[115],"our":[116,154],"algorithm":[117,175],"achieved":[118],"Pearson":[120],"correlation":[121,172],"coefficient":[122],"0.98.":[124],"Bland-Altman":[125],"analysis":[126],"demonstrated":[127],"bias":[129],"0.4":[131],"95%":[133],"limits":[134],"agreement":[136],"[-189.9-190.7]).":[138],"Our":[139],"linearly":[140],"weighted":[141],"Kappa":[142],"results":[143],"0.89":[145],"for":[146],"risk":[148],"category":[149],"assignment.":[150],"also":[152],"applied":[153],"very":[158],"(14,365":[160],"subjects)":[161],"cohort":[162],"National":[165],"Lung":[166],"Screening":[167],"Trial":[168],"(NLST).":[169],"demonstrate":[171],"predictions":[176],"cardiovascular-related":[178],"clinical":[179],"outcomes.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":4}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}