{"id":"https://openalex.org/W4220953714","doi":"https://doi.org/10.1117/12.2613298","title":"Size-reweighted cascaded fully convolutional network for substantia nigra segmentation from T2 MRI","display_name":"Size-reweighted cascaded fully convolutional network for substantia nigra segmentation from T2 MRI","publication_year":2022,"publication_date":"2022-03-18","ids":{"openalex":"https://openalex.org/W4220953714","doi":"https://doi.org/10.1117/12.2613298"},"language":"en","primary_location":{"id":"doi:10.1117/12.2613298","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2613298","pdf_url":null,"source":{"id":"https://openalex.org/S4363607561","display_name":"Medical Imaging 2022: Image Processing","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":"Medical Imaging 2022: Image Processing","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/A5100706806","display_name":"Tao Hu","orcid":"https://orcid.org/0009-0007-3757-9131"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tao Hu","raw_affiliation_strings":["Nagoya Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086595860","display_name":"Hayato Itoh","orcid":"https://orcid.org/0000-0002-1410-1078"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hayato Itoh","raw_affiliation_strings":["Nagoya Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074920808","display_name":"Masahiro Oda","orcid":"https://orcid.org/0000-0001-7714-422X"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahiro Oda","raw_affiliation_strings":["Nagoya Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059296576","display_name":"Shinji Saiki","orcid":null},"institutions":[{"id":"https://openalex.org/I34077901","display_name":"Juntendo University","ror":"https://ror.org/01692sz90","country_code":"JP","type":"education","lineage":["https://openalex.org/I34077901"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shinji Saiki","raw_affiliation_strings":["Juntendo Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Juntendo Univ. (Japan)","institution_ids":["https://openalex.org/I34077901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014705038","display_name":"Nobutaka Hattori","orcid":"https://orcid.org/0000-0002-2034-2556"},"institutions":[{"id":"https://openalex.org/I34077901","display_name":"Juntendo University","ror":"https://ror.org/01692sz90","country_code":"JP","type":"education","lineage":["https://openalex.org/I34077901"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nobutaka Hattori","raw_affiliation_strings":["Juntendo Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Juntendo Univ. (Japan)","institution_ids":["https://openalex.org/I34077901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090674915","display_name":"Koji Kamagata","orcid":"https://orcid.org/0000-0001-5028-218X"},"institutions":[{"id":"https://openalex.org/I34077901","display_name":"Juntendo University","ror":"https://ror.org/01692sz90","country_code":"JP","type":"education","lineage":["https://openalex.org/I34077901"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koji Kamagata","raw_affiliation_strings":["Juntendo Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Juntendo Univ. (Japan)","institution_ids":["https://openalex.org/I34077901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091368226","display_name":"Shigeki Aoki","orcid":"https://orcid.org/0000-0002-8491-0698"},"institutions":[{"id":"https://openalex.org/I34077901","display_name":"Juntendo University","ror":"https://ror.org/01692sz90","country_code":"JP","type":"education","lineage":["https://openalex.org/I34077901"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shigeki Aoki","raw_affiliation_strings":["Juntendo Univ. (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Juntendo Univ. (Japan)","institution_ids":["https://openalex.org/I34077901"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032527419","display_name":"Kensaku Mori","orcid":"https://orcid.org/0000-0002-0100-4797"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]},{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kensaku Mori","raw_affiliation_strings":["Nagoya Univ. (Japan)","National Institute of Informatics (Japan)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagoya Univ. (Japan)","institution_ids":["https://openalex.org/I60134161"]},{"raw_affiliation_string":"National Institute of Informatics (Japan)","institution_ids":["https://openalex.org/I184597095"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"7330","issue":null,"first_page":"125","last_page":"125"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9987000226974487,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9987000226974487,"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/T10816","display_name":"Cerebrovascular and Carotid Artery Diseases","score":0.9977999925613403,"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/T10227","display_name":"Acute Ischemic Stroke Management","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/computer-science","display_name":"Computer science","score":0.6785516142845154},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6714804172515869},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5417559146881104},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5251343250274658},{"id":"https://openalex.org/keywords/substantia-nigra","display_name":"Substantia nigra","score":0.49018436670303345},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48160573840141296},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.44959110021591187},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1405642032623291},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.06601768732070923}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6785516142845154},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6714804172515869},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5417559146881104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5251343250274658},{"id":"https://openalex.org/C2780938664","wikidata":"https://www.wikidata.org/wiki/Q753278","display_name":"Substantia nigra","level":4,"score":0.49018436670303345},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48160573840141296},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.44959110021591187},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1405642032623291},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.06601768732070923},{"id":"https://openalex.org/C2779734285","wikidata":"https://www.wikidata.org/wiki/Q11085","display_name":"Parkinson's disease","level":3,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2613298","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2613298","pdf_url":null,"source":{"id":"https://openalex.org/S4363607561","display_name":"Medical Imaging 2022: Image Processing","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":"Medical Imaging 2022: Image Processing","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":14,"referenced_works":["https://openalex.org/W1561072761","https://openalex.org/W1999514395","https://openalex.org/W2165382565","https://openalex.org/W2244833639","https://openalex.org/W2584227690","https://openalex.org/W2967248603","https://openalex.org/W3012429255","https://openalex.org/W3206402530","https://openalex.org/W6603220474","https://openalex.org/W6639824700","https://openalex.org/W6718240422","https://openalex.org/W6755137492","https://openalex.org/W6766318054","https://openalex.org/W6781033920"],"related_works":["https://openalex.org/W1975640329","https://openalex.org/W1572566098","https://openalex.org/W2374742110","https://openalex.org/W2387012743","https://openalex.org/W2047093218","https://openalex.org/W2034209754","https://openalex.org/W2374733173","https://openalex.org/W2761522158","https://openalex.org/W2033677771","https://openalex.org/W2027352134"],"abstract_inverted_index":{"Automatic":[0],"segmentation":[1,33,46,146,164],"of":[2,30,37,59,71,86,147,185,223],"the":[3,7,16,27,31,48,56,69,72,75,84,105,112,119,130,143,148,157,176,183,186,195,198,203,208,216,228],"Parkinson\u2019s":[4,87],"disease-related":[5],"tissue,":[6],"substantia":[8],"nigra":[9],"(SN),":[10],"is":[11,63,78,153],"an":[12],"important":[13],"step":[14],"towards":[15],"accurate":[17],"computer-aided":[18],"diagnosis":[19],"systems.":[20],"Recently":[21],"deep":[22,50],"learning":[23,51],"methods":[24],"have":[25],"achieved":[26],"state-of-the-art":[28],"performance":[29],"automated":[32],"in":[34,138,225],"various":[35],"scenarios":[36],"medical":[38],"image":[39],"analysis.":[40],"However,":[41],"to":[42,83,116,155,194,205],"acquire":[43],"high":[44,144],"resolution":[45,145,180],"results,":[47],"conventional":[49,131],"frameworks":[52],"depend":[53],"heavily":[54],"on":[55,182,207],"full":[57,179],"size":[58],"annotated":[60],"data,":[61],"which":[62,90],"pretty":[64],"time-consuming":[65],"and":[66,81,111,160],"expensive":[67],"for":[68,142],"training":[70],"model.":[73],"Moreover,":[74],"SN":[76,123,177,196,210],"structure":[77],"usually":[79],"tiny":[80,120,209],"sensitive":[82],"progression":[85],"disease":[88],"(PD),":[89],"brings":[91],"more":[92],"anatomic":[93],"variations":[94],"among":[95],"cases.":[96],"To":[97],"deal":[98],"with":[99,227],"these":[100],"problems,":[101],"this":[102],"paper":[103],"combines":[104],"cascaded":[106],"fully":[107],"convolutional":[108],"network":[109],"(FCN)":[110],"size-reweighted":[113,199],"loss":[114,200],"function":[115,201],"automatically":[117],"segment":[118],"subcortical":[121],"tissue":[122],"from":[124,129,166],"T2":[125],"MRI":[126,169],"volumes.":[127],"Different":[128],"one-stage":[132],"FCNs,":[133],"we":[134],"cascade":[135],"two":[136],"FCNs":[137],"a":[139,162,167],"coarse-to-fine":[140],"fashion":[141],"SN.":[149],"The":[150,171],"first":[151,187],"FCN":[152,173,218],"trained":[154],"locate":[156],"SN-contained":[158],"ROI":[159],"produce":[161],"coarse":[163],"mask":[165],"down-sampled":[168],"volume.":[170],"second":[172],"solely":[174],"segments":[175],"at":[178],"based":[181],"results":[184,213],"FCN.":[188],"Additionally,":[189],"by":[190],"giving":[191],"higher":[192],"weights":[193],"region,":[197],"encourages":[202],"model":[204,230],"concentrate":[206],"structure.":[211],"Our":[212],"showed":[214],"that":[215],"proposed":[217],"achieves":[219],"mean":[220],"dice":[221],"score":[222],"68.92%":[224],"comparison":[226],"baseline":[229],"66.40%.":[231]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
