{"id":"https://openalex.org/W4293038670","doi":"https://doi.org/10.1109/memea54994.2022.9856529","title":"Impact of network parameters on a U-Net based system for rectal cancer segmentation on MR images","display_name":"Impact of network parameters on a U-Net based system for rectal cancer segmentation on MR images","publication_year":2022,"publication_date":"2022-06-22","ids":{"openalex":"https://openalex.org/W4293038670","doi":"https://doi.org/10.1109/memea54994.2022.9856529"},"language":"en","primary_location":{"id":"doi:10.1109/memea54994.2022.9856529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea54994.2022.9856529","pdf_url":null,"source":{"id":"https://openalex.org/S4363605601","display_name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","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/A5002163911","display_name":"Jovana Pani\u0107","orcid":"https://orcid.org/0000-0002-6620-5610"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Jovana Panic","raw_affiliation_strings":["Polytechnic of Turin,Dept. of Electronics and Telecommunications,Torino,Italy","Dept. of Electronics and Telecommunications, Polytechnic of Turin, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Polytechnic of Turin,Dept. of Electronics and Telecommunications,Torino,Italy","institution_ids":["https://openalex.org/I177477856"]},{"raw_affiliation_string":"Dept. of Electronics and Telecommunications, Polytechnic of Turin, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088154061","display_name":"Valentina Giannini","orcid":"https://orcid.org/0000-0001-5052-8231"},"institutions":[{"id":"https://openalex.org/I4210151091","display_name":"Candiolo Cancer Institute","ror":"https://ror.org/04wadq306","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210151091","https://openalex.org/I4210153126","https://openalex.org/I4210167100"]},{"id":"https://openalex.org/I55143463","display_name":"University of Turin","ror":"https://ror.org/048tbm396","country_code":"IT","type":"education","lineage":["https://openalex.org/I55143463"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Valentina Giannini","raw_affiliation_strings":["University of Turin and Candiolo Cancer Institute, FPO-IRCCS,Dept. of Surgical Science,Torino,Italy","Dept. of Surgical Science, University of Turin and Candiolo Cancer Institute, FPO-IRCCS, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"University of Turin and Candiolo Cancer Institute, FPO-IRCCS,Dept. of Surgical Science,Torino,Italy","institution_ids":["https://openalex.org/I4210151091"]},{"raw_affiliation_string":"Dept. of Surgical Science, University of Turin and Candiolo Cancer Institute, FPO-IRCCS, Torino, Italy","institution_ids":["https://openalex.org/I4210151091","https://openalex.org/I55143463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014954401","display_name":"Arianna Defeudis","orcid":"https://orcid.org/0000-0002-1745-3044"},"institutions":[{"id":"https://openalex.org/I55143463","display_name":"University of Turin","ror":"https://ror.org/048tbm396","country_code":"IT","type":"education","lineage":["https://openalex.org/I55143463"]},{"id":"https://openalex.org/I4210151091","display_name":"Candiolo Cancer Institute","ror":"https://ror.org/04wadq306","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210151091","https://openalex.org/I4210153126","https://openalex.org/I4210167100"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Arianna Defeudis","raw_affiliation_strings":["University of Turin and Candiolo Cancer Institute, FPO-IRCCS,Dept. of Surgical Science,Torino,Italy","Dept. of Surgical Science, University of Turin and Candiolo Cancer Institute, FPO-IRCCS, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"University of Turin and Candiolo Cancer Institute, FPO-IRCCS,Dept. of Surgical Science,Torino,Italy","institution_ids":["https://openalex.org/I4210151091"]},{"raw_affiliation_string":"Dept. of Surgical Science, University of Turin and Candiolo Cancer Institute, FPO-IRCCS, Torino, Italy","institution_ids":["https://openalex.org/I4210151091","https://openalex.org/I55143463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066921477","display_name":"Daniele Regge","orcid":"https://orcid.org/0000-0001-8267-5279"},"institutions":[{"id":"https://openalex.org/I4210151091","display_name":"Candiolo Cancer Institute","ror":"https://ror.org/04wadq306","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210151091","https://openalex.org/I4210153126","https://openalex.org/I4210167100"]},{"id":"https://openalex.org/I55143463","display_name":"University of Turin","ror":"https://ror.org/048tbm396","country_code":"IT","type":"education","lineage":["https://openalex.org/I55143463"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Daniele Regge","raw_affiliation_strings":["University of Turin and Candiolo Cancer Institute, FPO-IRCCS,Dept. of Surgical Science,Torino,Italy","Dept. of Surgical Science, University of Turin and Candiolo Cancer Institute, FPO-IRCCS, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"University of Turin and Candiolo Cancer Institute, FPO-IRCCS,Dept. of Surgical Science,Torino,Italy","institution_ids":["https://openalex.org/I4210151091"]},{"raw_affiliation_string":"Dept. of Surgical Science, University of Turin and Candiolo Cancer Institute, FPO-IRCCS, Torino, Italy","institution_ids":["https://openalex.org/I4210151091","https://openalex.org/I55143463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011367557","display_name":"Gabriella Balestra","orcid":"https://orcid.org/0000-0003-2717-648X"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Gabriella Balestra","raw_affiliation_strings":["Polytechnic of Turin,Dept. of Electronics and Telecommunications,Torino,Italy","Dept. of Electronics and Telecommunications, Polytechnic of Turin, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Polytechnic of Turin,Dept. of Electronics and Telecommunications,Torino,Italy","institution_ids":["https://openalex.org/I177477856"]},{"raw_affiliation_string":"Dept. of Electronics and Telecommunications, Polytechnic of Turin, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012791314","display_name":"Samanta Rosati","orcid":"https://orcid.org/0000-0003-0620-594X"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Samanta Rosati","raw_affiliation_strings":["Polytechnic of Turin,Dept. of Electronics and Telecommunications,Torino,Italy","Dept. of Electronics and Telecommunications, Polytechnic of Turin, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Polytechnic of Turin,Dept. of Electronics and Telecommunications,Torino,Italy","institution_ids":["https://openalex.org/I177477856"]},{"raw_affiliation_string":"Dept. of Electronics and Telecommunications, Polytechnic of Turin, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5002163911"],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12432916,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9994999766349792,"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":0.9994999766349792,"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/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9976999759674072,"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/computer-science","display_name":"Computer science","score":0.6858841180801392},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.676588773727417},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6507759690284729},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6326507925987244},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.5853242874145508},{"id":"https://openalex.org/keywords/scope","display_name":"Scope (computer science)","score":0.5729647874832153},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5456985235214233},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5107026696205139},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5085998773574829},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.49398618936538696},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47753989696502686},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.45903468132019043},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4514722228050232},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.4510105550289154},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4435754716396332},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4309215247631073},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.42886680364608765},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4104308485984802},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3217581808567047},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1884552240371704},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1742074191570282},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1426067054271698},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.10455185174942017}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6858841180801392},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.676588773727417},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6507759690284729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6326507925987244},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.5853242874145508},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.5729647874832153},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5456985235214233},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5107026696205139},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5085998773574829},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.49398618936538696},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47753989696502686},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.45903468132019043},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4514722228050232},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.4510105550289154},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4435754716396332},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4309215247631073},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.42886680364608765},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4104308485984802},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3217581808567047},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1884552240371704},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1742074191570282},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1426067054271698},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.10455185174942017},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/memea54994.2022.9856529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea54994.2022.9856529","pdf_url":null,"source":{"id":"https://openalex.org/S4363605601","display_name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320323054","display_name":"Associazione Italiana per la Ricerca sul Cancro","ror":"https://ror.org/02g2x7380"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1899504021","https://openalex.org/W1901129140","https://openalex.org/W1970800786","https://openalex.org/W2014274213","https://openalex.org/W2408852305","https://openalex.org/W2734349601","https://openalex.org/W2806870995","https://openalex.org/W2899675781","https://openalex.org/W2905352294","https://openalex.org/W2946901414","https://openalex.org/W2968739673","https://openalex.org/W2989904326","https://openalex.org/W3016843157","https://openalex.org/W3016892711","https://openalex.org/W3046999841","https://openalex.org/W3082544002","https://openalex.org/W3127586369","https://openalex.org/W3157117078","https://openalex.org/W4200096693","https://openalex.org/W4200160717","https://openalex.org/W4200409353","https://openalex.org/W6713828333"],"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/W4200334192","https://openalex.org/W4391935352","https://openalex.org/W2952835238","https://openalex.org/W4283772513"],"abstract_inverted_index":{"The":[0,110],"use":[1],"of":[2,22,25,37,42,48,58,65,93,112,147,154,177,184,202],"Deep":[3],"Learning":[4],"(DL)":[5],"algorithms":[6],"in":[7,14,62],"the":[8,20,35,43,46,52,56,63,107,119,122,129,148,152,159,175,178,185,203],"medical":[9,206],"imaging":[10],"field":[11],"is":[12,142],"increasing":[13],"recent":[15],"years.":[16],"However,":[17],"they":[18],"require":[19],"selection":[21],"a":[23,59,91,99,181,190,199],"set":[24,192],"parameters":[26],"to":[27,87,102,105,117,174,198],"properly":[28,171],"perform.":[29],"In":[30],"this":[31,88],"study":[32],"we":[33],"evaluated":[34,149],"impact":[36],"three":[38],"factors":[39],"(the":[40],"construction":[41],"training":[44,191],"set,":[45],"number":[47],"network":[49],"layers":[50],"and":[51,81,104],"loss":[53,155],"function)":[54],"on":[55,71,194],"performance":[57],"U-Net":[60],"system":[61],"segmentation":[64],"Locally":[66],"Advanced":[67],"Rectal":[68],"Cancer":[69],"(LARC)":[70],"Magnetic":[72],"Resonance":[73],"Imaging":[74],"(MRI).":[75],"Images":[76],"from":[77],"3":[78],"different":[79,83],"institutions":[80],"4":[82],"scanners":[84,114],"were":[85,115,125],"used":[86,116],"scope,":[89],"for":[90,127],"total":[92],"100":[94],"patients.":[95],"All":[96],"images":[97],"underwent":[98],"pre-processing":[100],"step":[101],"normalize":[103],"highlight":[106],"tumoral":[108],"area.":[109],"sequences":[111,124],"two":[113],"construct":[118],"networks":[120],"while":[121],"remaining":[123],"employed":[126],"validating":[128],"best":[130],"performing":[131],"systems.":[132],"From":[133],"our":[134],"results,":[135],"it":[136,168],"emerged":[137],"that":[138],"Dice":[139],"Similarity":[140],"Coefficient":[141],"not":[143],"affected":[144],"by":[145],"any":[146],"factors.":[150],"Conversely,":[151],"choice":[153],"function":[156],"could":[157],"bias":[158],"results":[160],"towards":[161],"either":[162],"precision":[163],"or":[164],"recall":[165],"and,":[166],"thus,":[167],"should":[169],"be":[170],"performed":[172],"according":[173],"scope":[176],"network.":[179],"Moreover,":[180],"slightly":[182],"improvement":[183],"performances":[186],"was":[187],"observed":[188],"using":[189],"based":[193],"clustering,":[195],"maybe":[196],"due":[197],"better":[200],"representation":[201],"heterogeneity":[204],"characterizing":[205],"images.":[207]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}