{"id":"https://openalex.org/W2789826769","doi":"https://doi.org/10.1109/cisp-bmei.2017.8301983","title":"Segmentation of GBM in MRI images using an efficient speed function based on level set method","display_name":"Segmentation of GBM in MRI images using an efficient speed function based on level set method","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2789826769","doi":"https://doi.org/10.1109/cisp-bmei.2017.8301983","mag":"2789826769"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2017.8301983","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2017.8301983","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5079720685","display_name":"Alireza Mojtabavi","orcid":null},"institutions":[{"id":"https://openalex.org/I70640408","display_name":"Tehran University of Medical Sciences","ror":"https://ror.org/01c4pz451","country_code":"IR","type":"education","lineage":["https://openalex.org/I70640408"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Alireza Mojtabavi","raw_affiliation_strings":["Image-Guided Surgery Group, Tehran University of Medical Sciences, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Image-Guided Surgery Group, Tehran University of Medical Sciences, Tehran, Iran","institution_ids":["https://openalex.org/I70640408"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058816427","display_name":"Parastoo Farnia","orcid":"https://orcid.org/0000-0002-7554-5545"},"institutions":[{"id":"https://openalex.org/I70640408","display_name":"Tehran University of Medical Sciences","ror":"https://ror.org/01c4pz451","country_code":"IR","type":"education","lineage":["https://openalex.org/I70640408"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Parastoo Farnia","raw_affiliation_strings":["Image-Guided Surgery Group, Tehran University of Medical Sciences, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Image-Guided Surgery Group, Tehran University of Medical Sciences, Tehran, Iran","institution_ids":["https://openalex.org/I70640408"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009007390","display_name":"Alireza Ahmadian","orcid":"https://orcid.org/0000-0002-6394-9470"},"institutions":[{"id":"https://openalex.org/I70640408","display_name":"Tehran University of Medical Sciences","ror":"https://ror.org/01c4pz451","country_code":"IR","type":"education","lineage":["https://openalex.org/I70640408"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Alireza Ahmadian","raw_affiliation_strings":["Image-Guided Surgery Group, Tehran University of Medical Sciences, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Image-Guided Surgery Group, Tehran University of Medical Sciences, Tehran, Iran","institution_ids":["https://openalex.org/I70640408"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080020124","display_name":"M. Alimohamadi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210107967","display_name":"Sina Hospital","ror":"https://ror.org/01jqdqz10","country_code":"IR","type":"healthcare","lineage":["https://openalex.org/I4210107967"]},{"id":"https://openalex.org/I70640408","display_name":"Tehran University of Medical Sciences","ror":"https://ror.org/01c4pz451","country_code":"IR","type":"education","lineage":["https://openalex.org/I70640408"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Meysam Alimohamadi","raw_affiliation_strings":["Sina Specialized & Subspecialty Hospital, Tehran University of Medical Sciences, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Sina Specialized & Subspecialty Hospital, Tehran University of Medical Sciences, Tehran, Iran","institution_ids":["https://openalex.org/I4210107967","https://openalex.org/I70640408"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057320955","display_name":"Ahmad Pour\u2010Rashidi","orcid":"https://orcid.org/0000-0002-4544-5527"},"institutions":[{"id":"https://openalex.org/I4210107967","display_name":"Sina Hospital","ror":"https://ror.org/01jqdqz10","country_code":"IR","type":"healthcare","lineage":["https://openalex.org/I4210107967"]},{"id":"https://openalex.org/I70640408","display_name":"Tehran University of Medical Sciences","ror":"https://ror.org/01c4pz451","country_code":"IR","type":"education","lineage":["https://openalex.org/I70640408"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Ahmad Pourrashidi","raw_affiliation_strings":["Sina Specialized & Subspecialty Hospital, Tehran University of Medical Sciences, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Sina Specialized & Subspecialty Hospital, Tehran University of Medical Sciences, Tehran, Iran","institution_ids":["https://openalex.org/I4210107967","https://openalex.org/I70640408"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055253105","display_name":"Hamidreza Saligheh Rad","orcid":null},"institutions":[{"id":"https://openalex.org/I70640408","display_name":"Tehran University of Medical Sciences","ror":"https://ror.org/01c4pz451","country_code":"IR","type":"education","lineage":["https://openalex.org/I70640408"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Hamidreza Saligheh Rad","raw_affiliation_strings":["Image-Guided Surgery Group, Tehran University of Medical Sciences, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Image-Guided Surgery Group, Tehran University of Medical Sciences, Tehran, Iran","institution_ids":["https://openalex.org/I70640408"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086896369","display_name":"Javad Alirezaie","orcid":"https://orcid.org/0000-0001-7129-4825"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Javad Alirezaie","raw_affiliation_strings":["Department of Electrical Engineering, Ryerson University, Toronto, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Ryerson University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5079720685"],"corresponding_institution_ids":["https://openalex.org/I70640408"],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.5085628,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9984999895095825,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.996399998664856,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.8133460283279419},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6643387079238892},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6090264916419983},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.6024492383003235},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5983717441558838},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5787985920906067},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.5587728023529053},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.556388258934021},{"id":"https://openalex.org/keywords/level-set-method","display_name":"Level set method","score":0.5540788769721985},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.5434795022010803},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5223492383956909},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5145248770713806},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.45832645893096924},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.43648669123649597},{"id":"https://openalex.org/keywords/region-of-interest","display_name":"Region of interest","score":0.4194015562534332},{"id":"https://openalex.org/keywords/gold-standard","display_name":"Gold standard (test)","score":0.4147951602935791},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38277482986450195},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26746702194213867},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11059153079986572}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8133460283279419},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6643387079238892},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6090264916419983},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.6024492383003235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5983717441558838},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5787985920906067},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.5587728023529053},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.556388258934021},{"id":"https://openalex.org/C125269122","wikidata":"https://www.wikidata.org/wiki/Q1751397","display_name":"Level set method","level":4,"score":0.5540788769721985},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.5434795022010803},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5223492383956909},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5145248770713806},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.45832645893096924},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.43648669123649597},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.4194015562534332},{"id":"https://openalex.org/C40993552","wikidata":"https://www.wikidata.org/wiki/Q514654","display_name":"Gold standard (test)","level":2,"score":0.4147951602935791},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38277482986450195},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26746702194213867},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11059153079986572},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2017.8301983","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2017.8301983","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W119622245","https://openalex.org/W1561442812","https://openalex.org/W1815337875","https://openalex.org/W1975108959","https://openalex.org/W1982339756","https://openalex.org/W1991113069","https://openalex.org/W1999244633","https://openalex.org/W2003129478","https://openalex.org/W2011323163","https://openalex.org/W2026616100","https://openalex.org/W2063552084","https://openalex.org/W2073469994","https://openalex.org/W2077596487","https://openalex.org/W2102099319","https://openalex.org/W2116654471","https://openalex.org/W2124351162","https://openalex.org/W2127890285","https://openalex.org/W2148798129","https://openalex.org/W2148977460","https://openalex.org/W2150134853","https://openalex.org/W2169527406","https://openalex.org/W2169551590","https://openalex.org/W4212949515"],"related_works":["https://openalex.org/W4402926319","https://openalex.org/W4389060404","https://openalex.org/W2973136608","https://openalex.org/W3012828488","https://openalex.org/W4286233748","https://openalex.org/W4254054209","https://openalex.org/W2367921179","https://openalex.org/W3080476861","https://openalex.org/W657288383","https://openalex.org/W3198334642"],"abstract_inverted_index":{"Accurate":[0],"segmentation":[1,32,48,90,155,208],"and":[2,43,85,102,149,171,177,188],"characterization":[3],"of":[4,16,26,50,70,82,116,156,169,182,206,229],"abnormalities":[5],"in":[6,13,23],"brain":[7],"tumor":[8,118],"are":[9,173],"challenging":[10],"task,":[11],"especially":[12],"the":[14,20,24,64,103,108,117,126,167,196,199,204],"case":[15],"GBM":[17,89,139,157,207],"tumors,":[18],"where":[19],"ambiguities":[21],"presented":[22],"boundaries":[25,65],"these":[27],"tumors":[28],"necessitates":[29],"using":[30,120,141],"efficient":[31],"method.":[33],"Level":[34],"set":[35,79,101,215],"methods":[36],"have":[37],"proven":[38],"to":[39,60,66,106,164,193,212,227],"be":[40],"a":[41,55,76,133],"flexible":[42],"powerful":[44],"tool":[45],"for":[46,88,111],"image":[47],"because":[49],"being":[51],"shape-driven":[52],"method":[53,202,216,223],"with":[54,138,217],"properly":[56],"defined":[57],"speed":[58,95,220],"function":[59,96],"grow":[61],"or":[62],"shrink":[63],"segment":[67],"complex":[68],"objects":[69],"interest,":[71],"precisely.":[72],"In":[73],"this":[74],"study":[75],"combined":[77,201],"level":[78,100,214],"algorithm":[80],"consists":[81],"both":[83],"region":[84,119],"boundary":[86],"terms":[87],"is":[91,158,224],"proposed.":[92],"The":[93,180],"modified":[94],"incorporates":[97],"threshold":[98,218],"based":[99,219],"Laplacian":[104],"filter":[105],"highlight":[107],"fine":[109],"details":[110],"performing":[112],"an":[113],"accurate":[114],"extraction":[115],"multiple":[121],"seed":[122],"points":[123],"selected":[124],"by":[125,140,175,209],"user.":[127],"An":[128],"evaluation":[129],"was":[130],"performed":[131],"on":[132],"dataset":[134],"containing":[135],"6":[136],"patients":[137],"three":[142],"measures":[143],"Dice,":[144],"false":[145,150],"positive":[146],"error":[147,152],"(FPE)":[148],"negative":[151],"(FNE).":[153],"Manual":[154],"considered":[159],"as":[160],"gold":[161,189],"standard.":[162],"Compared":[163],"traditional":[165],"method,":[166],"mean":[168,181],"FPE":[170],"FNE":[172],"improved":[174],"53.5%":[176],"53.1%,":[178],"respectively.":[179],"Dice":[183],"coefficients":[184],"between":[185],"our":[186],"results":[187,197],"standard":[190],"measurement":[191],"reached":[192],"0.88.":[194],"As":[195],"proved,":[198],"proposed":[200],"improves":[203],"accuracy":[205],"16%":[210],"compared":[211],"conventional":[213],"function.":[221],"Our":[222],"also":[225],"robust":[226],"change":[228],"parameters.":[230]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-25T21:42:39.735039","created_date":"2025-10-10T00:00:00"}
