{"id":"https://openalex.org/W4416874533","doi":"https://doi.org/10.1109/ispa66905.2025.11259457","title":"Assessing the Impact of Automatic vs. Manual Segmentation on Radiomic Feature Analysis: A Prostate Cancer Study","display_name":"Assessing the Impact of Automatic vs. Manual Segmentation on Radiomic Feature Analysis: A Prostate Cancer Study","publication_year":2025,"publication_date":"2025-10-29","ids":{"openalex":"https://openalex.org/W4416874533","doi":"https://doi.org/10.1109/ispa66905.2025.11259457"},"language":null,"primary_location":{"id":"doi:10.1109/ispa66905.2025.11259457","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispa66905.2025.11259457","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 14th International Symposium on Image and Signal Processing and Analysis (ISPA)","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/A5022396990","display_name":"Bruno Mendes","orcid":"https://orcid.org/0000-0002-7574-7630"},"institutions":[{"id":"https://openalex.org/I182534213","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612","country_code":"PT","type":"education","lineage":["https://openalex.org/I182534213"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Bruno Mendes","raw_affiliation_strings":["Faculdade de Engenharia da Universidade do Porto (FEUP),Centro de Investiga&#x00E7;&#x00E3;o do IPO do Porto,Porto,Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculdade de Engenharia da Universidade do Porto (FEUP),Centro de Investiga&#x00E7;&#x00E3;o do IPO do Porto,Porto,Portugal","institution_ids":["https://openalex.org/I182534213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101961906","display_name":"In\u00eas Domingues","orcid":"https://orcid.org/0000-0002-2334-7280"},"institutions":[{"id":"https://openalex.org/I83863532","display_name":"Polytechnic Institute of Porto","ror":"https://ror.org/04988re48","country_code":"PT","type":"education","lineage":["https://openalex.org/I83863532"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"In\u00eas Domingues","raw_affiliation_strings":["Polytechnic University of Coimbra,Centro de Investiga&#x00E7;&#x00E3;o do IPO do Porto,Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Polytechnic University of Coimbra,Centro de Investiga&#x00E7;&#x00E3;o do IPO do Porto,Portugal","institution_ids":["https://openalex.org/I83863532"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082299802","display_name":"Jo\u00e3o Santos","orcid":"https://orcid.org/0000-0003-2465-5143"},"institutions":[{"id":"https://openalex.org/I182534213","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612","country_code":"PT","type":"education","lineage":["https://openalex.org/I182534213"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Jo\u00e3o Santos","raw_affiliation_strings":["Instituto de Ci&#x00EA;ncias Biom&#x00E9;dicas Abel Salazar (ICBAS),Centro de Investiga&#x00E7;&#x00E3;o do IPO do Porto,Porto,Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto de Ci&#x00EA;ncias Biom&#x00E9;dicas Abel Salazar (ICBAS),Centro de Investiga&#x00E7;&#x00E3;o do IPO do Porto,Porto,Portugal","institution_ids":["https://openalex.org/I182534213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.51140652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"22","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10124","display_name":"Prostate Cancer Diagnosis and Treatment","score":0.45089998841285706,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T10124","display_name":"Prostate Cancer Diagnosis and Treatment","score":0.45089998841285706,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T10358","display_name":"Advanced Radiotherapy Techniques","score":0.2328999936580658,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"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":0.21950000524520874,"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/segmentation","display_name":"Segmentation","score":0.7128000259399414},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6233000159263611},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5680999755859375},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5121999979019165},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45730000734329224},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4544000029563904},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.43050000071525574}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7239000201225281},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7128000259399414},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6233000159263611},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.59170001745224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5680999755859375},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5121999979019165},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45730000734329224},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4544000029563904},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.43050000071525574},{"id":"https://openalex.org/C2780192828","wikidata":"https://www.wikidata.org/wiki/Q181257","display_name":"Prostate cancer","level":3,"score":0.3919999897480011},{"id":"https://openalex.org/C122048520","wikidata":"https://www.wikidata.org/wiki/Q2913954","display_name":"Percentile","level":2,"score":0.383899986743927},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.37860000133514404},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3677000105381012},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.2906000018119812},{"id":"https://openalex.org/C40993552","wikidata":"https://www.wikidata.org/wiki/Q514654","display_name":"Gold standard (test)","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26330000162124634},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C2776235491","wikidata":"https://www.wikidata.org/wiki/Q9625","display_name":"Prostate","level":3,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ispa66905.2025.11259457","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispa66905.2025.11259457","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 14th International Symposium on Image and Signal Processing and Analysis (ISPA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2041365664","https://openalex.org/W2128739912","https://openalex.org/W2340422569","https://openalex.org/W2767128594","https://openalex.org/W2998789541","https://openalex.org/W3209458182"],"related_works":[],"abstract_inverted_index":{"Radiomics,":[0],"the":[1,28,42,61,77,140,158,181],"extraction":[2],"of":[3,44,63,172,197],"features":[4,109],"from":[5,83,112],"radiographic":[6],"images":[7],"using":[8,122],"data-characterization":[9],"algorithms,":[10],"has":[11],"gained":[12],"considerable":[13],"attention":[14],"in":[15],"prostate":[16,105],"cancer":[17,106],"research.":[18],"Traditionally,":[19],"manual":[20,156,214],"segmentation":[21,49,114,206],"conducted":[22],"by":[23,54,117],"experts":[24],"is":[25,34],"regarded":[26],"as":[27],"gold":[29],"standard.":[30],"However,":[31],"this":[32,64,73],"method":[33],"time-consuming,":[35],"subjective,":[36],"and":[37,57,100,120,145,219],"susceptible":[38],"to":[39,213],"variability,":[40],"affecting":[41],"performance":[43,212],"classification":[45,68,121,211],"models.":[46],"Deep":[47],"learning-based":[48],"presents":[50],"a":[51,166,190],"promising":[52],"alternative":[53],"offering":[55],"fast":[56],"reproducible":[58],"results":[59],"but":[60],"impact":[62],"approach":[65],"on":[66,103],"radiomics-based":[67],"models":[69,127],"remains":[70],"unexplored.":[71],"In":[72],"study,":[74],"we":[75],"evaluated":[76],"differences":[78],"between":[79],"manually":[80],"drawn":[81],"contours":[82],"an":[84,170,195],"External":[85],"Beam":[86],"Radiotherapy":[87],"(EBRT)":[88],"planning":[89],"system":[90],"with":[91,129,149,165,189,207],"automatically":[92],"generated":[93],"You":[94],"Only":[95],"Look":[96],"Once":[97],"(YOLO)":[98],"segmentations":[99],"their":[101],"effects":[102],"radiomic-based":[104],"classification.":[107],"Radiomic":[108],"were":[110],"extracted":[111],"both":[113],"approaches,":[115],"followed":[116],"feature":[118,131,163,187],"selection":[119,132,164,188],"14":[123],"different":[124],"machine":[125],"learning":[126],"combined":[128],"7":[130],"techniques.":[133],"Performance":[134],"was":[135],"assessed":[136],"through":[137],"Area":[138],"Under":[139],"Receiver":[141],"Operating":[142],"Characteristic":[143],"(AUC)":[144],"Accuracy":[146],"(ACC)":[147],"metrics":[148],"five-fold":[150],"cross-validation.":[151],"Results":[152],"showed":[153],"that":[154,204],"for":[155],"segmentation,":[157,180],"best":[159,182],"model":[160,183],"used":[161],"Percentile":[162],"Bagging(ExtraTree)":[167],"classifier,":[168,193],"achieving":[169],"AUC":[171,196],"<tex":[173],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[174],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$0.78":[175],"\\pm":[176],"0.12$</tex>.":[177],"For":[178],"YOLO-based":[179],"employed":[184],"Variance":[185],"Threshold":[186],"Gradient":[191],"Boosting":[192],"obtaining":[194],"0.75":[198],"\u00b1":[199],"0.04.":[200],"These":[201],"findings":[202],"suggest":[203],"automatic":[205],"YOLO":[208],"yields":[209],"comparable":[210],"delineation":[215],"while":[216],"improving":[217],"efficiency":[218],"reproducibility.":[220]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-12-01T00:00:00"}