{"id":"https://openalex.org/W1575783590","doi":"https://doi.org/10.1109/isbi.2015.7163822","title":"Radiomics texture feature extraction for characterizing GBM phenotypes using GLCM","display_name":"Radiomics texture feature extraction for characterizing GBM phenotypes using GLCM","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1575783590","doi":"https://doi.org/10.1109/isbi.2015.7163822","mag":"1575783590"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2015.7163822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7163822","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)","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/A5024700033","display_name":"Ahmad Chaddad","orcid":"https://orcid.org/0000-0003-3402-9576"},"institutions":[{"id":"https://openalex.org/I1343551460","display_name":"The University of Texas MD Anderson Cancer Center","ror":"https://ror.org/04twxam07","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1343551460"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ahmad Chaddad","raw_affiliation_strings":["Department of Diagnostic Radiology MD Anderson Cancer Center University of Texas, USA","Department of Diagnostic Radiology, MD Anderson Cancer Center, University of Texas, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Diagnostic Radiology MD Anderson Cancer Center University of Texas, USA","institution_ids":["https://openalex.org/I1343551460"]},{"raw_affiliation_string":"Department of Diagnostic Radiology, MD Anderson Cancer Center, University of Texas, USA","institution_ids":["https://openalex.org/I1343551460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072374777","display_name":"Pascal O. Zinn","orcid":"https://orcid.org/0000-0003-0091-5887"},"institutions":[{"id":"https://openalex.org/I181547552","display_name":"Baylor College of Medicine","ror":"https://ror.org/02pttbw34","country_code":"US","type":"education","lineage":["https://openalex.org/I181547552","https://openalex.org/I2801539370"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pascal O. Zinn","raw_affiliation_strings":["Department of Neurosurgery Baylor College of Medicine, USA","Department of Neurosurgery, Baylor College of Medicine, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Neurosurgery Baylor College of Medicine, USA","institution_ids":["https://openalex.org/I181547552"]},{"raw_affiliation_string":"Department of Neurosurgery, Baylor College of Medicine, USA","institution_ids":["https://openalex.org/I181547552"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087117639","display_name":"Rivka R. Colen","orcid":"https://orcid.org/0000-0002-0882-0607"},"institutions":[{"id":"https://openalex.org/I1343551460","display_name":"The University of Texas MD Anderson Cancer Center","ror":"https://ror.org/04twxam07","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1343551460"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rivka R. Colen","raw_affiliation_strings":["Department of Diagnostic Radiology MD Anderson Cancer Center University of Texas, USA","Department of Diagnostic Radiology, MD Anderson Cancer Center, University of Texas, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Diagnostic Radiology MD Anderson Cancer Center University of Texas, USA","institution_ids":["https://openalex.org/I1343551460"]},{"raw_affiliation_string":"Department of Diagnostic Radiology, MD Anderson Cancer Center, University of Texas, USA","institution_ids":["https://openalex.org/I1343551460"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"84","last_page":"87"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9883000254631042,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9853000044822693,"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/radiomics","display_name":"Radiomics","score":0.8099141120910645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6821574568748474},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6810283660888672},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6427154541015625},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6089906096458435},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5857027173042297},{"id":"https://openalex.org/keywords/phenotype","display_name":"Phenotype","score":0.5574402213096619},{"id":"https://openalex.org/keywords/glioblastoma","display_name":"Glioblastoma","score":0.529396653175354},{"id":"https://openalex.org/keywords/gray-level","display_name":"Gray level","score":0.5234512686729431},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.49874281883239746},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4935868978500366},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4935098886489868},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4461541771888733},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.4314349293708801},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.17570707201957703},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.12920978665351868},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.11982426047325134},{"id":"https://openalex.org/keywords/cancer-research","display_name":"Cancer research","score":0.1125175952911377},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.10723230242729187},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10353481769561768},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.05895915627479553}],"concepts":[{"id":"https://openalex.org/C2778559731","wikidata":"https://www.wikidata.org/wiki/Q23808793","display_name":"Radiomics","level":2,"score":0.8099141120910645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6821574568748474},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6810283660888672},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6427154541015625},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6089906096458435},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5857027173042297},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.5574402213096619},{"id":"https://openalex.org/C2776194525","wikidata":"https://www.wikidata.org/wiki/Q282142","display_name":"Glioblastoma","level":2,"score":0.529396653175354},{"id":"https://openalex.org/C2985861186","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Gray level","level":3,"score":0.5234512686729431},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.49874281883239746},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4935868978500366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4935098886489868},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4461541771888733},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.4314349293708801},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.17570707201957703},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.12920978665351868},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.11982426047325134},{"id":"https://openalex.org/C502942594","wikidata":"https://www.wikidata.org/wiki/Q3421914","display_name":"Cancer research","level":1,"score":0.1125175952911377},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.10723230242729187},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10353481769561768},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.05895915627479553},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2015.7163822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7163822","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W51291072","https://openalex.org/W1565377632","https://openalex.org/W1594031697","https://openalex.org/W1912982817","https://openalex.org/W1965797467","https://openalex.org/W1995068921","https://openalex.org/W2034644725","https://openalex.org/W2061997187","https://openalex.org/W2088317370","https://openalex.org/W2114589799","https://openalex.org/W2116531017","https://openalex.org/W2153563443","https://openalex.org/W2170051899","https://openalex.org/W2316943511","https://openalex.org/W2330820318","https://openalex.org/W2482589566","https://openalex.org/W6602084134","https://openalex.org/W6649115558","https://openalex.org/W6672884768","https://openalex.org/W6699051108"],"related_works":["https://openalex.org/W3000891326","https://openalex.org/W4205100762","https://openalex.org/W2605851261","https://openalex.org/W2734724112","https://openalex.org/W4321251649","https://openalex.org/W3128847470","https://openalex.org/W2909044173","https://openalex.org/W2555360349","https://openalex.org/W172934006","https://openalex.org/W2002821148"],"abstract_inverted_index":{"Glioblastoma":[0],"(GBM)":[1],"is":[2,9,104],"a":[3],"markedly":[4],"heterogeneous":[5],"brain":[6],"tumor":[7,19],"and":[8,20,42],"composed":[10],"of":[11,33,75],"three":[12],"main":[13],"volumetric":[14],"phenotypes,":[15],"namely,":[16],"necrosis,":[17],"active":[18],"edema,":[21],"identifiable":[22],"on":[23,62,82,101],"magnetic":[24],"resonance":[25],"imaging":[26],"(MRI).":[27],"This":[28],"paper":[29],"assesses":[30],"the":[31,34,83,88,97,102],"usefulness":[32],"GBM":[35,59,79,108],"features":[36],"detection":[37],"by":[38],"using":[39,87],"semi-automatic":[40],"segmentation":[41],"texture":[43,84,93,98],"feature":[44,85,99],"extracted":[45],"from":[46],"gray":[47],"level":[48],"co-occurrence":[49],"matrix":[50],"(GLCM).":[51],"Feature":[52],"vectors":[53],"are":[54],"then":[55],"used":[56],"for":[57,69,77],"predicting":[58],"phenotypes":[60,80],"based":[61,81,100],"nearest":[63],"neighbors":[64],"(NN)":[65],"classifier.":[66],"Simulation":[67],"results":[68],"22":[70],"patients":[71],"show":[72],"an":[73],"accuracy":[74],"75.58%":[76],"distinguishing":[78],"selection":[86],"decision":[89],"trees":[90],"model.":[91],"Preliminary":[92],"analysis":[94],"demonstrated":[95],"that":[96],"GLCM":[103],"promising":[105],"to":[106],"distinguish":[107],"phenotypes.":[109]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}