{"id":"https://openalex.org/W7160308481","doi":"https://doi.org/10.5753/sbsi.2026.248301","title":"Improving the quality of information systems for diagnosis: an approach to detecting and correcting segmentation errors","display_name":"Improving the quality of information systems for diagnosis: an approach to detecting and correcting segmentation errors","publication_year":2026,"publication_date":"2026-05-05","ids":{"openalex":"https://openalex.org/W7160308481","doi":"https://doi.org/10.5753/sbsi.2026.248301"},"language":null,"primary_location":{"id":"doi:10.5753/sbsi.2026.248301","is_oa":false,"landing_page_url":"https://doi.org/10.5753/sbsi.2026.248301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Brazilian Symposium on Information Systems (SBSI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5118125040","display_name":"Bruno F. Raquel","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131481","display_name":"Universidad San Pedro","ror":"https://ror.org/03fehwj53","country_code":"PE","type":"education","lineage":["https://openalex.org/I4210131481"]}],"countries":["PE"],"is_corresponding":false,"raw_author_name":"Bruno F. Raquel","raw_affiliation_strings":["USP"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"USP","institution_ids":["https://openalex.org/I4210131481"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135372075","display_name":"Matheus A. O. Ribeiro","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131481","display_name":"Universidad San Pedro","ror":"https://ror.org/03fehwj53","country_code":"PE","type":"education","lineage":["https://openalex.org/I4210131481"]}],"countries":["PE"],"is_corresponding":false,"raw_author_name":"Matheus A. O. Ribeiro","raw_affiliation_strings":["USP"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"USP","institution_ids":["https://openalex.org/I4210131481"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054257245","display_name":"F\u00e1tima L. S. Nunes","orcid":"https://orcid.org/0000-0003-0040-0752"},"institutions":[{"id":"https://openalex.org/I4210131481","display_name":"Universidad San Pedro","ror":"https://ror.org/03fehwj53","country_code":"PE","type":"education","lineage":["https://openalex.org/I4210131481"]}],"countries":["PE"],"is_corresponding":false,"raw_author_name":"F\u00e1tima L. S. Nunes","raw_affiliation_strings":["USP"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"USP","institution_ids":["https://openalex.org/I4210131481"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210131481"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.54479098,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"101","last_page":"120"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.20440000295639038,"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":0.20440000295639038,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.09000000357627869,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.05490000173449516,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7558000087738037},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5371000170707703},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5274999737739563},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.5184999704360962},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.46070000529289246},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4514999985694885},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4253999888896942},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.3822999894618988},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.34040001034736633}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7558000087738037},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7134000062942505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6087999939918518},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5371000170707703},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5274999737739563},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.5184999704360962},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.46070000529289246},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4514999985694885},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4449999928474426},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43220001459121704},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4253999888896942},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.3822999894618988},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.34040001034736633},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.33250001072883606},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.3174999952316284},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3167000114917755},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C106436119","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assurance","level":3,"score":0.29580000042915344},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C3019060180","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automated method","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.25450000166893005},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2517000138759613},{"id":"https://openalex.org/C172849965","wikidata":"https://www.wikidata.org/wiki/Q3148875","display_name":"Reference frame","level":3,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5753/sbsi.2026.248301","is_oa":false,"landing_page_url":"https://doi.org/10.5753/sbsi.2026.248301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Brazilian Symposium on Information Systems (SBSI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7557395696640015,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W13904108","https://openalex.org/W1998543880","https://openalex.org/W2013187361","https://openalex.org/W2092574121","https://openalex.org/W2130538955","https://openalex.org/W2158167845","https://openalex.org/W2274227799","https://openalex.org/W2590070005","https://openalex.org/W2594608309","https://openalex.org/W2752595895","https://openalex.org/W2763147268","https://openalex.org/W2804047627","https://openalex.org/W2908633263","https://openalex.org/W2930326546","https://openalex.org/W2954299637","https://openalex.org/W2965191493","https://openalex.org/W3002592716","https://openalex.org/W3102100346","https://openalex.org/W3112385165","https://openalex.org/W3134287839","https://openalex.org/W3164469844","https://openalex.org/W3209877123","https://openalex.org/W4205513034","https://openalex.org/W4206113990","https://openalex.org/W4213454781","https://openalex.org/W4293248242","https://openalex.org/W4296440938","https://openalex.org/W4318540737","https://openalex.org/W4366609137","https://openalex.org/W4377690951","https://openalex.org/W4382940736","https://openalex.org/W4383377291","https://openalex.org/W4405316215","https://openalex.org/W4411169740","https://openalex.org/W4411212533"],"related_works":[],"abstract_inverted_index":{"Research":[0,138],"Context:":[1],"The":[2,140,169],"development":[3],"of":[4,10,103,134,167,233,244],"automated":[5,38,234],"Information":[6,135,222],"Systems":[7,223],"(IS)":[8],"capable":[9],"segmenting":[11],"the":[12,110,113,117,132,156,188,191,221,231,242,247],"left":[13],"ventricle":[14],"(LV)":[15],"in":[16,84,109,131,241],"cardiac":[17,86],"magnetic":[18],"resonance":[19],"imaging":[20],"(MRI)":[21],"and":[22,49,64,80,151,212],"estimating":[23],"clinically":[24],"relevant":[25],"biomarkers":[26],"is":[27,93,129,260],"fundamental":[28],"to":[29,105,178,203,214,220,253],"support":[30],"diagnostic":[31],"decision-making.":[32],"Scientific":[33],"and/or":[34,68],"Practical":[35],"Problem:":[36],"Many":[37],"IS":[39,76,125,215],"based":[40],"on":[41,60,144,180],"deep":[42],"learning":[43],"(DL)":[44],"are":[45],"not":[46],"fully":[47],"reliable":[48],"lack":[50],"dedicated":[51],"modules":[52],"for":[53,75,162,184,237],"error":[54],"detection,":[55],"which":[56],"makes":[57],"them":[58],"dependent":[59],"constant":[61],"manual":[62],"inspection":[63],"correction.":[65],"Proposed":[66],"Solution":[67],"Analysis:":[69],"We":[70],"propose":[71],"a":[72,227],"post-processing":[73],"method":[74,141,170,228],"that":[77,229],"automatically":[78],"detects":[79],"corrects":[81],"segmentation":[82,196],"errors":[83],"LV":[85,145,245],"MRI":[87,104],"produced":[88],"by":[89,95,120,225],"DL":[90,153],"systems.":[91],"Detection":[92],"performed":[94],"combining":[96],"metrics":[97],"computed":[98],"between":[99],"consecutive":[100],"time":[101,164],"frames":[102],"identify":[106],"inconsistent":[107],"segmentations":[108,146,161],"temporal":[111],"dimension;":[112],"correction":[114,189],"step":[115],"reconstructs":[116],"problematic":[118],"frame":[119],"interpolating":[121],"nearby":[122],"segmentations.":[123,210],"Related":[124],"Theory:":[126],"This":[127,217],"work":[128],"grounded":[130],"perspectives":[133],"Processing":[136],"Theory.":[137],"Method:":[139],"was":[142],"validated":[143,240],"containing":[147],"both":[148],"artificially":[149],"generated":[150],"real":[152,181],"errors,":[154],"using":[155],"LVQuan19":[157],"dataset":[158],"with":[159,174,208],"reference":[160,209],"all":[163],"instants.":[165],"Summary":[166],"Results:":[168],"achieved":[171],"detection":[172],"performance":[173],"F1-score":[175],"values":[176,201],"up":[177],"0.99":[179],"data,":[182],"particularly":[183],"severe":[185],"errors.":[186],"Regarding":[187],"step,":[190],"selected":[192],"strategy":[193],"effectively":[194],"improved":[195],"consistency,":[197],"achieving":[198],"Dice":[199],"coefficient":[200],"close":[202],"0.95,":[204],"indicating":[205],"excellent":[206],"agreement":[207],"Contributions":[211],"Impact":[213],"area:":[216],"study":[218],"contributes":[219],"field":[224],"introducing":[226],"improves":[230],"reliability":[232],"computer-aided":[235],"systems":[236],"diagnosis.":[238],"Although":[239],"context":[243],"segmentation,":[246],"proposed":[248],"approach":[249],"can":[250],"be":[251],"applied":[252],"other":[254],"domains":[255],"where":[256],"sequential":[257],"data":[258],"consistency":[259],"critical.":[261]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-05-06T00:00:00"}