{"id":"https://openalex.org/W3110052512","doi":"https://doi.org/10.1109/iwbis50925.2020.9255593","title":"Segmentation and Approximation of Blood Volume in Intracranial Hemorrhage Patients Based on Computed Tomography Scan Images Using Deep Learning Method","display_name":"Segmentation and Approximation of Blood Volume in Intracranial Hemorrhage Patients Based on Computed Tomography Scan Images Using Deep Learning Method","publication_year":2020,"publication_date":"2020-10-17","ids":{"openalex":"https://openalex.org/W3110052512","doi":"https://doi.org/10.1109/iwbis50925.2020.9255593","mag":"3110052512"},"language":"en","primary_location":{"id":"doi:10.1109/iwbis50925.2020.9255593","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwbis50925.2020.9255593","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Workshop on Big Data and Information Security (IWBIS)","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/A5047641285","display_name":"Kezia Irene","orcid":null},"institutions":[{"id":"https://openalex.org/I29617571","display_name":"University of Indonesia","ror":"https://ror.org/0116zj450","country_code":"ID","type":"education","lineage":["https://openalex.org/I29617571"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Kezia Irene","raw_affiliation_strings":["Faculty of Computer Science Universitas Indonesia Kampus Baru UI Depok, Jawa Barat, Indonesia"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science Universitas Indonesia Kampus Baru UI Depok, Jawa Barat, Indonesia","institution_ids":["https://openalex.org/I29617571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048298559","display_name":"M. Anwar Ma\u2019sum","orcid":"https://orcid.org/0000-0002-9251-7781"},"institutions":[{"id":"https://openalex.org/I29617571","display_name":"University of Indonesia","ror":"https://ror.org/0116zj450","country_code":"ID","type":"education","lineage":["https://openalex.org/I29617571"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"M. Anwar Ma'sum","raw_affiliation_strings":["Faculty of Computer Science Universitas Indonesia Kampus Baru UI Depok, Jawa Barat, Indonesia"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science Universitas Indonesia Kampus Baru UI Depok, Jawa Barat, Indonesia","institution_ids":["https://openalex.org/I29617571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035134518","display_name":"Reyhan Eddy Yunus","orcid":"https://orcid.org/0000-0001-9046-6303"},"institutions":[{"id":"https://openalex.org/I29617571","display_name":"University of Indonesia","ror":"https://ror.org/0116zj450","country_code":"ID","type":"education","lineage":["https://openalex.org/I29617571"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Reyhan Eddy Yunus","raw_affiliation_strings":["Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia"],"affiliations":[{"raw_affiliation_string":"Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia","institution_ids":["https://openalex.org/I29617571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069933043","display_name":"Wisnu Jatmiko","orcid":"https://orcid.org/0000-0002-0530-7955"},"institutions":[{"id":"https://openalex.org/I29617571","display_name":"University of Indonesia","ror":"https://ror.org/0116zj450","country_code":"ID","type":"education","lineage":["https://openalex.org/I29617571"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Wisnu Jatmiko","raw_affiliation_strings":["Faculty of Computer Science Universitas Indonesia Kampus Baru UI Depok, Jawa Barat, Indonesia"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science Universitas Indonesia Kampus Baru UI Depok, Jawa Barat, Indonesia","institution_ids":["https://openalex.org/I29617571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5047641285"],"corresponding_institution_ids":["https://openalex.org/I29617571"],"apc_list":null,"apc_paid":null,"fwci":0.6867,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.66757525,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":97},"biblio":{"volume":"14","issue":null,"first_page":"65","last_page":"72"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9675999879837036,"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"}},"topics":[{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9675999879837036,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9643999934196472,"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/T11763","display_name":"Intracerebral and Subarachnoid Hemorrhage Research","score":0.963699996471405,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"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/upsampling","display_name":"Upsampling","score":0.7338534593582153},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6328312158584595},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6292570233345032},{"id":"https://openalex.org/keywords/traumatic-brain-injury","display_name":"Traumatic brain injury","score":0.563752293586731},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5620654821395874},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5060750842094421},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.48990386724472046},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.45185625553131104},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.4333202838897705},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.4101768136024475},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3315674662590027}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.7338534593582153},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6328312158584595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6292570233345032},{"id":"https://openalex.org/C2781017439","wikidata":"https://www.wikidata.org/wiki/Q1995526","display_name":"Traumatic brain injury","level":2,"score":0.563752293586731},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5620654821395874},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5060750842094421},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.48990386724472046},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.45185625553131104},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4333202838897705},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.4101768136024475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3315674662590027},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwbis50925.2020.9255593","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwbis50925.2020.9255593","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Workshop on Big Data and Information Security (IWBIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8600000143051147}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W317170363","https://openalex.org/W1964357740","https://openalex.org/W1969020732","https://openalex.org/W1974327622","https://openalex.org/W1991964403","https://openalex.org/W2016769329","https://openalex.org/W2054533649","https://openalex.org/W2067448822","https://openalex.org/W2097763239","https://openalex.org/W2201728905","https://openalex.org/W2332066482","https://openalex.org/W2343172899","https://openalex.org/W2522738478","https://openalex.org/W2560609797","https://openalex.org/W2563701462","https://openalex.org/W2598379669","https://openalex.org/W2607490533","https://openalex.org/W2883545264","https://openalex.org/W2890546378","https://openalex.org/W2898842944","https://openalex.org/W2905307056","https://openalex.org/W2944090748","https://openalex.org/W2950366791","https://openalex.org/W2969667256","https://openalex.org/W2979750740","https://openalex.org/W2980285142","https://openalex.org/W2990544317","https://openalex.org/W3104258355","https://openalex.org/W3105950366","https://openalex.org/W3152413988","https://openalex.org/W3157358945","https://openalex.org/W4211064847","https://openalex.org/W6760149902","https://openalex.org/W6763422710"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W2790662084","https://openalex.org/W3208266890","https://openalex.org/W3091976719"],"abstract_inverted_index":{"Traumatic":[0],"brain":[1,16,26,160],"injury":[2,6,27,161],"is":[3,28,32,51],"a":[4,52,166,193,198,219,226],"common":[5],"that":[7],"can":[8,78],"range":[9],"from":[10,106,151],"mild":[11],"concussions":[12],"to":[13,59,66,81],"severe":[14,21],"permanent":[15],"damage.":[17],"One":[18],"of":[19,54,102,145,195,200,230],"the":[20,61,117,131,152,179,186,206,212],"damages":[22],"caused":[23],"by":[24,35,165,175],"traumatic":[25,159],"intracranial":[29,88,103],"hemorrhage,":[30],"which":[31],"typically":[33],"diagnosed":[34],"clinicians":[36,55,83],"using":[37,110,211],"head":[38,147],"computed":[39],"tomography":[40],"(CT)":[41],"scans.":[42],"However,":[43],"in":[44,47,84,185,192],"some":[45],"hospitals":[46],"Indonesia,":[48],"sometimes":[49],"there":[50],"lack":[53],"who":[56],"are":[57,209],"able":[58],"interpret":[60],"CT":[62,107,148],"scan":[63,108],"results,":[64],"leading":[65],"morbidity":[67],"and":[68,98,113,129,197],"mortality.":[69],"Deep":[70],"learning":[71,112],"algorithms,":[72],"especially":[73],"convolutional":[74],"neural":[75],"networks":[76],"(CNN)":[77],"be":[79],"utilized":[80,121,136],"help":[82],"diagnosing":[85],"patients":[86,105],"with":[87,218,225],"hemorrhage.":[89],"In":[90],"this":[91,142],"study,":[92],"we":[93,120,135,171],"propose":[94],"an":[95],"automated":[96],"segmentation":[97],"blood":[99,118,132,169,203],"volume":[100,133,204],"approximation":[101],"hemorrhage":[104],"images":[109],"deep":[111],"regression":[114,137],"methods.":[115,138],"For":[116,168,202],"segmentation,":[119,170],"Dynamic":[122],"Graph":[123],"Convolutional":[124],"Neural":[125],"Network":[126],"(DGCNN)":[127],"architecture":[128],"for":[130,141],"approximation,":[134,205],"The":[139,181],"dataset":[140],"work":[143],"consists":[144],"27":[146],"scans":[149],"obtained":[150,184,210],"Cipto":[153],"Mangunkusumo":[154],"National":[155],"General":[156],"Hospital":[157],"2019":[158],"data":[162],"segmented":[163],"manually":[164],"radiologist.":[167],"proposed":[172],"several":[173],"scenarios":[174],"upsampling":[176,190],"or":[177],"downsampling":[178],"data.":[180],"best":[182,207],"results":[183,208],"scenario":[187],"without":[188],"doing":[189],"resulted":[191],"sensitivity":[194],"97.8%":[196],"specificity":[199],"95.6%.":[201],"support":[213],"vector":[214],"machine":[215],"(SVM)":[216],"method":[217],"radial":[220],"basis":[221],"function":[222],"(RBF)":[223],"kernel,":[224],"mean":[227],"squared":[228],"error":[229],"3.67x10":[231],"<sup":[232],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[233],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">\u2227</sup>":[234],"4.":[235]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}