{"id":"https://openalex.org/W4379251616","doi":"https://doi.org/10.48550/arxiv.2306.00047","title":"Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning","display_name":"Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning","publication_year":2023,"publication_date":"2023-05-31","ids":{"openalex":"https://openalex.org/W4379251616","doi":"https://doi.org/10.48550/arxiv.2306.00047"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2306.00047","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.00047","pdf_url":"https://arxiv.org/pdf/2306.00047","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2306.00047","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037133367","display_name":"Ruining Deng","orcid":"https://orcid.org/0000-0001-6300-8518"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Ruining","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100727824","display_name":"Yanwei Li","orcid":"https://orcid.org/0000-0002-2736-132X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yanwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102795939","display_name":"Peize Li","orcid":"https://orcid.org/0000-0002-5321-2176"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Peize","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100727959","display_name":"Jiacheng Wang","orcid":"https://orcid.org/0000-0003-1252-8761"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jiacheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058681839","display_name":"Lucas W. Remedios","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Remedios, Lucas W.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092081203","display_name":"Saydolimkhon Agzamkhodjaev","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Agzamkhodjaev, Saydolimkhon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074197453","display_name":"Zuhayr Asad","orcid":"https://orcid.org/0000-0002-2401-5026"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Asad, Zuhayr","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100414574","display_name":"Quan Liu","orcid":"https://orcid.org/0000-0002-8710-1810"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Quan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100736899","display_name":"Can Cui","orcid":"https://orcid.org/0009-0009-7082-3444"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Can","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Wang, Yaohong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yaohong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Wang, Yihan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yihan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037478865","display_name":"Yucheng Tang","orcid":"https://orcid.org/0000-0002-6008-9700"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Yucheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115589666","display_name":"Haichun Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Haichun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067191302","display_name":"Yuankai Huo","orcid":"https://orcid.org/0000-0002-2096-8065"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huo, Yuankai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9979000091552734,"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":0.8459354639053345},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7500302791595459},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.7296825051307678},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.700812041759491},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5355837941169739},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5243903994560242},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4438946843147278},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43664103746414185},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43369078636169434},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4195285737514496},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.37745237350463867},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35349729657173157},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3421483337879181},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32902634143829346}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8459354639053345},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7500302791595459},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.7296825051307678},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.700812041759491},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5355837941169739},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5243903994560242},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4438946843147278},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43664103746414185},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43369078636169434},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4195285737514496},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37745237350463867},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35349729657173157},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3421483337879181},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32902634143829346},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2306.00047","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.00047","pdf_url":"https://arxiv.org/pdf/2306.00047","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2306.00047","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2306.00047","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2306.00047","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.00047","pdf_url":"https://arxiv.org/pdf/2306.00047","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G398763758","display_name":null,"funder_award_id":"R01DK135597","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5993123900","display_name":null,"funder_award_id":"R01DK135597","funder_id":"https://openalex.org/F4320337357","funder_display_name":"National Institute of Diabetes and Digestive and Kidney Diseases"},{"id":"https://openalex.org/G6273532412","display_name":null,"funder_award_id":"DK56942","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337357","display_name":"National Institute of Diabetes and Digestive and Kidney Diseases","ror":"https://ror.org/00adh9b73"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4379251616.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2358755282","https://openalex.org/W2625833328","https://openalex.org/W1533177136","https://openalex.org/W4380994516","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Multi-class":[0],"cell":[1,41,91,219],"segmentation":[2,92,113,148,193],"in":[3],"high-resolution":[4],"Giga-pixel":[5,104],"whole":[6],"slide":[7],"images":[8],"(WSI)":[9],"is":[10,36,80,142,173],"critical":[11],"for":[12,89],"various":[13],"clinical":[14],"applications.":[15],"Training":[16],"such":[17,34],"an":[18],"AI":[19,63],"model":[20,195],"typically":[21],"requires":[22],"labor-intensive":[23],"pixel-wise":[24],"manual":[25],"annotation":[26,35],"from":[27,96,169,182],"experienced":[28,130,183],"domain":[29,73],"experts":[30],"(e.g.,":[31,43],"pathologists).":[32],"Moreover,":[33],"error-prone":[37],"when":[38],"differentiating":[39],"fine-grained":[40],"types":[42],"podocyte":[44],"and":[45,111,218],"mesangial":[46],"cells)":[47],"via":[48,122],"the":[49,58,147,156,188,197,205],"naked":[50],"human":[51],"eye.":[52],"In":[53],"this":[54,78],"study,":[55],"we":[56],"assess":[57],"feasibility":[59],"of":[60,77,190],"democratizing":[61],"pathological":[62,192],"deployment":[64],"by":[65],"only":[66],"using":[67,93,150,166],"lay":[68,97,124,170,198],"annotators":[69,125],"(annotators":[70],"without":[71],"medical":[72],"knowledge).":[74],"The":[75,100,215],"contribution":[76],"paper":[79],"threefold:":[81],"(1)":[82],"We":[83],"proposed":[84,101,143],"a":[85,191,210],"molecular-empowered":[86],"learning":[87,136,160,206],"scheme":[88],"multi-class":[90],"partial":[94],"labels":[95],"annotators;":[98],"(2)":[99],"method":[102,141,161,186],"integrated":[103],"level":[105],"molecular-morphology":[106],"cross-modality":[107],"registration,":[108],"molecular-informed":[109,167],"annotation,":[110],"molecular-oriented":[112],"model,":[114],"so":[115],"as":[116,126],"to":[117,144,196,209],"achieve":[118],"significantly":[119],"superior":[120],"performance":[121,149],"3":[123],"compared":[127],"with":[128,138],"2":[129],"pathologists;":[131],"(3)":[132],"A":[133],"deep":[134,194],"corrective":[135],"(learning":[137],"imperfect":[139],"label)":[140],"further":[145],"improve":[146],"partially":[151],"annotated":[152],"noisy":[153],"data.":[154],"From":[155],"experimental":[157],"results,":[158],"our":[159],"achieved":[162],"F1":[163],"=":[164,180],"0.8496":[165],"annotations":[168,178,220],"annotators,":[171],"which":[172,201],"better":[174],"than":[175],"conventional":[176],"morphology-based":[177],"(F1":[179],"0.7015)":[181],"pathologists.":[184],"Our":[185],"democratizes":[187],"development":[189],"annotator":[199],"level,":[200],"consequently":[202],"scales":[203],"up":[204],"process":[207],"similar":[208],"non-medical":[211],"computer":[212],"vision":[213],"task.":[214],"official":[216],"implementation":[217],"are":[221],"publicly":[222],"available":[223],"at":[224],"https://github.com/hrlblab/MolecularEL.":[225]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2023-06-04T00:00:00"}
