{"id":"https://openalex.org/W2921919863","doi":"https://doi.org/10.1117/12.2512911","title":"Generalization of tumor identification algorithms","display_name":"Generalization of tumor identification algorithms","publication_year":2019,"publication_date":"2019-03-18","ids":{"openalex":"https://openalex.org/W2921919863","doi":"https://doi.org/10.1117/12.2512911","mag":"2921919863"},"language":"en","primary_location":{"id":"doi:10.1117/12.2512911","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2512911","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Digital Pathology","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":null,"display_name":"Muhammad Khalid Khan Niazi","orcid":null},"institutions":[{"id":"https://openalex.org/I47251452","display_name":"Wake Forest University","ror":"https://ror.org/0207ad724","country_code":"US","type":"education","lineage":["https://openalex.org/I47251452"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Muhammad Khalid Khan Niazi","raw_affiliation_strings":["Ctr. for Biomedical Informatics, Wake Forest School of Medicine (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ctr. for Biomedical Informatics, Wake Forest School of Medicine (United States)","institution_ids":["https://openalex.org/I47251452"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045373968","display_name":"Thomas E. Tavolara","orcid":"https://orcid.org/0000-0001-6455-3120"},"institutions":[{"id":"https://openalex.org/I47251452","display_name":"Wake Forest University","ror":"https://ror.org/0207ad724","country_code":"US","type":"education","lineage":["https://openalex.org/I47251452"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas E. Tavolara","raw_affiliation_strings":["Ctr. for Biomedical Informatics, Wake Forest School of Medicine (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ctr. for Biomedical Informatics, Wake Forest School of Medicine (United States)","institution_ids":["https://openalex.org/I47251452"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007518961","display_name":"\u00c7a\u011flar \u015eenaras","orcid":"https://orcid.org/0000-0003-4211-4367"},"institutions":[{"id":"https://openalex.org/I47251452","display_name":"Wake Forest University","ror":"https://ror.org/0207ad724","country_code":"US","type":"education","lineage":["https://openalex.org/I47251452"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Caglar Senaras","raw_affiliation_strings":["Ctr. for Biomedical Informatics, Wake Forest School of Medicine (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ctr. for Biomedical Informatics, Wake Forest School of Medicine (United States)","institution_ids":["https://openalex.org/I47251452"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012016433","display_name":"Gary Tozbikian","orcid":"https://orcid.org/0000-0002-5941-5652"},"institutions":[{"id":"https://openalex.org/I2802841970","display_name":"The Ohio State University Wexner Medical Center","ror":"https://ror.org/00c01js51","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I2802841970"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gary Tozbikian","raw_affiliation_strings":["The Ohio State Univ. Wexner Medical Ctr. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Ohio State Univ. Wexner Medical Ctr. (United States)","institution_ids":["https://openalex.org/I2802841970"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015029502","display_name":"Douglas J. Hartman","orcid":"https://orcid.org/0000-0001-8962-8993"},"institutions":[{"id":"https://openalex.org/I4210134769","display_name":"University of Pittsburgh Medical Center","ror":"https://ror.org/04ehecz88","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210098814","https://openalex.org/I4210134769"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Douglas J. Hartman","raw_affiliation_strings":["Univ. of Pittsburgh Medical Ctr. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Pittsburgh Medical Ctr. (United States)","institution_ids":["https://openalex.org/I4210134769"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037372125","display_name":"Vidya Arole","orcid":"https://orcid.org/0009-0006-8553-1741"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vidya Arole","raw_affiliation_strings":["The Ohio State Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Ohio State Univ. (United States)","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028342220","display_name":"Liron Pantanowitz","orcid":"https://orcid.org/0000-0001-8182-5503"},"institutions":[{"id":"https://openalex.org/I4210134769","display_name":"University of Pittsburgh Medical Center","ror":"https://ror.org/04ehecz88","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210098814","https://openalex.org/I4210134769"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liron Pantanowitz","raw_affiliation_strings":["Univ. of Pittsburgh Medical Ctr. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Pittsburgh Medical Ctr. (United States)","institution_ids":["https://openalex.org/I4210134769"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077316017","display_name":"Metin N. G\u00fcrcan","orcid":"https://orcid.org/0000-0002-2421-8229"},"institutions":[{"id":"https://openalex.org/I47251452","display_name":"Wake Forest University","ror":"https://ror.org/0207ad724","country_code":"US","type":"education","lineage":["https://openalex.org/I47251452"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Metin N. Gurcan","raw_affiliation_strings":["Ctr. for Biomedical Informatics, Wake Forest School of Medicine (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ctr. for Biomedical Informatics, Wake Forest School of Medicine (United States)","institution_ids":["https://openalex.org/I47251452"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4374,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.64820416,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"10581","issue":null,"first_page":"34","last_page":"34"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":1.0,"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":1.0,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9948999881744385,"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"}},{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9876000285148621,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5646902322769165},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5293755531311035},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5031775832176208},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.5031456351280212},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44859352707862854},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4430179297924042},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.4357852339744568},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.43443387746810913},{"id":"https://openalex.org/keywords/neuroendocrine-tumors","display_name":"Neuroendocrine tumors","score":0.42730221152305603},{"id":"https://openalex.org/keywords/biopsy","display_name":"Biopsy","score":0.4207276701927185},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2490018606185913},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.23842740058898926},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.16203609108924866},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11833864450454712}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5646902322769165},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5293755531311035},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5031775832176208},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.5031456351280212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44859352707862854},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4430179297924042},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.4357852339744568},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.43443387746810913},{"id":"https://openalex.org/C2779066768","wikidata":"https://www.wikidata.org/wiki/Q1981276","display_name":"Neuroendocrine tumors","level":2,"score":0.42730221152305603},{"id":"https://openalex.org/C2775934546","wikidata":"https://www.wikidata.org/wiki/Q179991","display_name":"Biopsy","level":2,"score":0.4207276701927185},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2490018606185913},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.23842740058898926},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.16203609108924866},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11833864450454712},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2512911","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2512911","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Digital Pathology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1578387260","https://openalex.org/W1989843455","https://openalex.org/W2004779027","https://openalex.org/W2037402988","https://openalex.org/W2638976208","https://openalex.org/W2784905247","https://openalex.org/W2796854304","https://openalex.org/W2893153797","https://openalex.org/W4234552385","https://openalex.org/W4254648668","https://openalex.org/W6608727978","https://openalex.org/W6659995096","https://openalex.org/W6676297131","https://openalex.org/W6686164453","https://openalex.org/W6698072841","https://openalex.org/W6747753682","https://openalex.org/W6754880003"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W3162204513","https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W2359952343","https://openalex.org/W2239445980","https://openalex.org/W2080152487","https://openalex.org/W3083152911","https://openalex.org/W3022347918"],"abstract_inverted_index":{"The":[0],"morphological":[1],"features":[2],"that":[3,70,101],"pathologists":[4],"use":[5],"to":[6,14,35,47,74,83,111,133,142,171,191],"differentiate":[7],"neoplasms":[8],"from":[9,77,86,114,137,178],"normal":[10],"tissue":[11,15],"are":[12,168],"nonspecific":[13],"type.":[16],"For":[17],"example,":[18],"if":[19],"given":[20],"a":[21,30,107,143,153],"Ki67":[22,118],"stained":[23,119],"biopsy":[24],"of":[25,51,98,145,157,176,181,196,205],"neuroendocrine":[26,120],"or":[27],"breast":[28,135],"tumor,":[29],"pathologist":[31],"would":[32],"be":[33,81],"able":[34,82],"correctly":[36],"identify":[37,48,84],"morphologically":[38],"abnormal":[39],"cells":[40],"in":[41,117],"both":[42,52],"samples":[43],"but":[44],"may":[45],"struggle":[46],"the":[49,96,127,169,189,194,203,206],"origin":[50,182],"samples.":[53],"This":[54,68,186],"is":[55],"also":[56],"true":[57],"for":[58],"other":[59,87],"pathological":[60],"malignancies":[61],"such":[62],"as":[63,200,202],"carcinomas,":[64],"sarcomas,":[65],"and":[66],"leukemia.":[67],"implies":[69],"computer":[71],"algorithms":[72,199],"trained":[73],"recognize":[75],"tumor":[76,85,91,113,121,197],"one":[78],"site":[79],"should":[80],"sites":[88,180],"with":[89,193],"similar":[90],"subtypes.":[92],"Here,":[93],"we":[94,125],"present":[95],"results":[97,167],"an":[99],"experiment":[100],"supports":[102],"this":[103],"hypothesis.":[104],"We":[105],"train":[106],"deep":[108,130],"learning":[109,131],"system":[110,151],"distinguish":[112,134],"non-tumor":[115],"regions":[116],"digital":[122],"slides.":[123],"Then,":[124],"test":[126],"same,":[128],"unmodified,":[129],"model":[132],"cancer":[136],"non-cancer":[138],"regions.":[139],"When":[140],"applied":[141],"sample":[144],"96":[146],"high":[147],"power":[148],"fields,":[149],"our":[150,164,166],"achieved":[152],"cumulative":[154],"pixel-wise":[155],"accuracy":[156],"86%":[158],"across":[159],"these":[160],"high-power":[161],"fields.":[162],"To":[163],"knowledge,":[165],"first":[170],"formally":[172],"demonstrate":[173],"generalized":[174],"segmentation":[175],"tumors":[177],"different":[179],"through":[183],"image":[184],"analysis.":[185],"paradigm":[187],"has":[188],"potential":[190],"help":[192],"design":[195],"identification":[198],"well":[201],"composition":[204],"datasets":[207],"they":[208],"draw":[209],"from.":[210]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
