{"id":"https://openalex.org/W4412645362","doi":"https://doi.org/10.3389/frai.2025.1618426","title":"Thyroid nodule segmentation in ultrasound images using transformer models with masked autoencoder pre-training","display_name":"Thyroid nodule segmentation in ultrasound images using transformer models with masked autoencoder pre-training","publication_year":2025,"publication_date":"2025-07-24","ids":{"openalex":"https://openalex.org/W4412645362","doi":"https://doi.org/10.3389/frai.2025.1618426","pmid":"https://pubmed.ncbi.nlm.nih.gov/40777517"},"language":"en","primary_location":{"id":"doi:10.3389/frai.2025.1618426","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2025.1618426","pdf_url":"https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1618426/pdf","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1618426/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027424271","display_name":"Yi Xiang","orcid":"https://orcid.org/0000-0003-2118-4825"},"institutions":[{"id":"https://openalex.org/I157582758","display_name":"SingHealth","ror":"https://ror.org/04me94w47","country_code":"SG","type":"healthcare","lineage":["https://openalex.org/I157582758"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Yi Xiang","raw_affiliation_strings":["Office of Insights & Analytics, Division of Digital Strategy, SingHealth, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Office of Insights & Analytics, Division of Digital Strategy, SingHealth, Singapore, Singapore","institution_ids":["https://openalex.org/I157582758"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Rajendra Acharya","orcid":null},"institutions":[{"id":"https://openalex.org/I185523456","display_name":"University of Southern Queensland","ror":"https://ror.org/04sjbnx57","country_code":"AU","type":"education","lineage":["https://openalex.org/I185523456"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Rajendra Acharya","raw_affiliation_strings":["School of Mathematics, Physics and Computing, University of Southern Queensland, Springfield Central, QLD, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, Physics and Computing, University of Southern Queensland, Springfield Central, QLD, Australia","institution_ids":["https://openalex.org/I185523456"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113659944","display_name":"Le Quan","orcid":"https://orcid.org/0009-0002-9787-2464"},"institutions":[{"id":"https://openalex.org/I2251586001","display_name":"Singapore General Hospital","ror":"https://ror.org/036j6sg82","country_code":"SG","type":"healthcare","lineage":["https://openalex.org/I2251586001"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Quan Le","raw_affiliation_strings":["Data Science and Artificial Intelligence Lab, Singapore General Hospital, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science and Artificial Intelligence Lab, Singapore General Hospital, Singapore, Singapore","institution_ids":["https://openalex.org/I2251586001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077976730","display_name":"Jen Hong Tan","orcid":"https://orcid.org/0000-0002-7785-2987"},"institutions":[{"id":"https://openalex.org/I2251586001","display_name":"Singapore General Hospital","ror":"https://ror.org/036j6sg82","country_code":"SG","type":"healthcare","lineage":["https://openalex.org/I2251586001"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jen Hong Tan","raw_affiliation_strings":["Data Science and Artificial Intelligence Lab, Singapore General Hospital, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science and Artificial Intelligence Lab, Singapore General Hospital, Singapore, Singapore","institution_ids":["https://openalex.org/I2251586001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008446614","display_name":"Chiaw Ling Chng","orcid":"https://orcid.org/0000-0003-2232-5298"},"institutions":[{"id":"https://openalex.org/I2251586001","display_name":"Singapore General Hospital","ror":"https://ror.org/036j6sg82","country_code":"SG","type":"healthcare","lineage":["https://openalex.org/I2251586001"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chiaw-Ling Chng","raw_affiliation_strings":["Department of Endocrinology, Singapore General Hospital, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Endocrinology, Singapore General Hospital, Singapore, Singapore","institution_ids":["https://openalex.org/I2251586001"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027424271"],"corresponding_institution_ids":["https://openalex.org/I157582758"],"apc_list":{"value":1150,"currency":"USD","value_usd":1150},"apc_paid":{"value":1150,"currency":"USD","value_usd":1150},"fwci":5.1157,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.95972251,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"1618426","last_page":"1618426"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10329","display_name":"Thyroid Cancer Diagnosis and Treatment","score":0.8716999888420105,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"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/T10329","display_name":"Thyroid Cancer Diagnosis and Treatment","score":0.8716999888420105,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"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/T10862","display_name":"AI in cancer detection","score":0.06560000032186508,"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"}},{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.010499999858438969,"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/computer-science","display_name":"Computer science","score":0.7223759293556213},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6904538869857788},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6555222868919373},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5303070545196533},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5014240741729736},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48169073462486267},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4551534354686737},{"id":"https://openalex.org/keywords/thyroid-nodules","display_name":"Thyroid nodules","score":0.4477868676185608},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33210644125938416},{"id":"https://openalex.org/keywords/thyroid","display_name":"Thyroid","score":0.10473242402076721}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7223759293556213},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6904538869857788},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6555222868919373},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5303070545196533},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5014240741729736},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48169073462486267},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4551534354686737},{"id":"https://openalex.org/C2779022025","wikidata":"https://www.wikidata.org/wiki/Q53829","display_name":"Thyroid nodules","level":3,"score":0.4477868676185608},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33210644125938416},{"id":"https://openalex.org/C526584372","wikidata":"https://www.wikidata.org/wiki/Q16399","display_name":"Thyroid","level":2,"score":0.10473242402076721},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/frai.2025.1618426","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2025.1618426","pdf_url":"https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1618426/pdf","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},{"id":"pmid:40777517","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40777517","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in artificial intelligence","raw_type":null},{"id":"pmh:oai:doaj.org/article:fd10f5776d954c82a296171487754767","is_oa":true,"landing_page_url":"https://doaj.org/article/fd10f5776d954c82a296171487754767","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Artificial Intelligence, Vol 8 (2025)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12328416","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12328416","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Front Artif Intell","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3389/frai.2025.1618426","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2025.1618426","pdf_url":"https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1618426/pdf","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320316262","display_name":"Duke-NUS Medical School","ror":"https://ror.org/02j1m6098"},{"id":"https://openalex.org/F4320320761","display_name":"Singapore General Hospital","ror":"https://ror.org/036j6sg82"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412645362.pdf","grobid_xml":"https://content.openalex.org/works/W4412645362.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1987273303","https://openalex.org/W1999478155","https://openalex.org/W2027685755","https://openalex.org/W2085279201","https://openalex.org/W2798122215","https://openalex.org/W2883547127","https://openalex.org/W3094502228","https://openalex.org/W3127751679","https://openalex.org/W3165252795","https://openalex.org/W3200379731","https://openalex.org/W4205687621","https://openalex.org/W4236965008","https://openalex.org/W4288089799","https://openalex.org/W4310055988","https://openalex.org/W4313156423","https://openalex.org/W4377088910","https://openalex.org/W4390822082","https://openalex.org/W6640054144","https://openalex.org/W6769627184"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2803255133","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W4405887298"],"abstract_inverted_index":{"Introduction:":[0],"Thyroid":[1],"nodule":[2,56,73,100,226],"segmentation":[3,246],"in":[4,18,55],"ultrasound":[5],"(US)":[6],"images":[7],"is":[8,95],"a":[9,15,68,108,125],"valuable":[10],"yet":[11,217],"challenging":[12],"task,":[13],"playing":[14],"critical":[16,199],"role":[17],"diagnosing":[19],"thyroid":[20,36,72,119],"cancer.":[21],"The":[22],"difficulty":[23],"arises":[24],"from":[25,85],"factors":[26],"such":[27],"as":[28],"the":[29,35,86,140,158],"absence":[30],"of":[31,47,166],"prior":[32],"knowledge":[33],"about":[34],"region,":[37],"low":[38],"contrast":[39],"between":[40,132],"anatomical":[41],"structures,":[42],"and":[43,52,122,134,144,169,174,194,211,225,239],"speckle":[44],"noise,":[45],"all":[46],"which":[48,94],"obscure":[49],"boundary":[50],"detection":[51],"introduce":[53],"variability":[54],"appearance":[57],"across":[58],"different":[59],"images.":[60],"Methods:":[61],"To":[62],"address":[63],"these":[64],"challenges,":[65],"we":[66],"propose":[67],"transformer-based":[69],"model":[70,159],"for":[71,97],"segmentation.":[74],"Unlike":[75],"traditional":[76],"convolutional":[77],"neural":[78],"networks":[79],"(CNNs),":[80],"transformers":[81],"capture":[82],"global":[83],"context":[84],"first":[87,106],"layer,":[88],"enabling":[89],"more":[90,198],"comprehensive":[91],"image":[92],"representation,":[93],"crucial":[96],"identifying":[98],"subtle":[99],"boundaries.":[101],"In":[102],"this":[103],"study,":[104],"We":[105],"pre-train":[107],"Masked":[109],"Autoencoder":[110],"(MAE)":[111],"to":[112,128,243],"reconstruct":[113],"masked":[114],"patches,":[115],"then":[116],"fine-tune":[117],"on":[118,139,171,232],"US":[120],"data,":[121,235],"further":[123,244],"explore":[124],"cross-attention":[126,184,237],"mechanism":[127],"enhance":[129],"information":[130],"flow":[131],"encoder":[133],"decoder.":[135],"Results:":[136],"Our":[137],"experiments":[138],"public":[141],"AIMI,":[142,172],"TN3K,":[143,173],"DDTI":[145],"datasets":[146],"show":[147],"that":[148,191],"MAE":[149,205],"pre-training":[150,206,236],"accelerates":[151],"convergence.":[152],"However,":[153],"overall":[154,218],"improvements":[155],"are":[156],"modest:":[157],"achieves":[160],"Dice":[161],"Similarity":[162],"Coefficient":[163],"(DSC)":[164],"scores":[165],"0.63,":[167],"0.64,":[168],"0.65":[170],"DDTI,":[175],"respectively,":[176],"highlighting":[177],"limitations":[178],"under":[179],"small-sample":[180],"conditions.":[181],"Furthermore,":[182],"adding":[183],"did":[185],"not":[186],"yield":[187],"consistent":[188],"gains,":[189],"suggesting":[190],"data":[192,224],"volume":[193],"diversity":[195],"may":[196],"be":[197],"than":[200],"additional":[201],"architectural":[202],"complexity.":[203],"Discussion:":[204],"notably":[207],"reduces":[208],"training":[209],"time":[210],"helps":[212],"themodel":[213],"learn":[214],"transferable":[215],"features,":[216],"accuracy":[219],"remains":[220],"constrained":[221],"by":[222],"limited":[223],"variability.":[227],"Future":[228],"work":[229],"will":[230],"focus":[231],"scaling":[233],"up":[234],"layers,":[238],"exploring":[240],"hybrid":[241],"architectures":[242],"boost":[245],"performance.":[247]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}