{"id":"https://openalex.org/W2305684009","doi":"https://doi.org/10.1117/12.2216632","title":"Nucleus segmentation in histology images with hierarchical multilevel thresholding","display_name":"Nucleus segmentation in histology images with hierarchical multilevel thresholding","publication_year":2016,"publication_date":"2016-03-23","ids":{"openalex":"https://openalex.org/W2305684009","doi":"https://doi.org/10.1117/12.2216632","mag":"2305684009"},"language":"en","primary_location":{"id":"doi:10.1117/12.2216632","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2216632","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/A5068090976","display_name":"Hady Ahmady Phoulady","orcid":"https://orcid.org/0000-0002-3215-7630"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hady Ahmady Phoulady","raw_affiliation_strings":["Univ. of South Florida (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of South Florida (United States)","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053211631","display_name":"Dmitry B. Goldgof","orcid":"https://orcid.org/0000-0001-5461-863X"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dmitry B. Goldgof","raw_affiliation_strings":["Univ. of South Florida (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of South Florida (United States)","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000168449","display_name":"Lawrence Hall","orcid":"https://orcid.org/0000-0002-7898-8456"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lawrence O. Hall","raw_affiliation_strings":["Univ. of South Florida (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of South Florida (United States)","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038456790","display_name":"Peter R. Mouton","orcid":"https://orcid.org/0000-0002-1008-4055"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter R. Mouton","raw_affiliation_strings":["Univ. of South Florida (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of South Florida (United States)","institution_ids":["https://openalex.org/I2613432"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.9496,"has_fulltext":false,"cited_by_count":59,"citation_normalized_percentile":{"value":0.97361062,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"9791","issue":null,"first_page":"979111","last_page":"979111"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998000264167786,"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":0.9998000264167786,"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":0.996999979019165,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9944000244140625,"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":0.8234877586364746},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7531548738479614},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7266285419464111},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.680332362651825},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6627293229103088},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6432960033416748},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5815117359161377},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4518279433250427},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43352729082107544},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3308260142803192}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8234877586364746},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7531548738479614},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7266285419464111},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.680332362651825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6627293229103088},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6432960033416748},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5815117359161377},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4518279433250427},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43352729082107544},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3308260142803192},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2216632","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2216632","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6600000262260437,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1597336200","https://openalex.org/W1970120446","https://openalex.org/W2043034051","https://openalex.org/W2057114171","https://openalex.org/W2080363053","https://openalex.org/W2081578499","https://openalex.org/W2133059825","https://openalex.org/W2133866056","https://openalex.org/W2138957397","https://openalex.org/W2142332605","https://openalex.org/W6635816984","https://openalex.org/W6680396984"],"related_works":["https://openalex.org/W1968965685","https://openalex.org/W2012792772","https://openalex.org/W2356573839","https://openalex.org/W2009028679","https://openalex.org/W2357424838","https://openalex.org/W2327601824","https://openalex.org/W2161102362","https://openalex.org/W1705110471","https://openalex.org/W2106833984","https://openalex.org/W2020103936"],"abstract_inverted_index":{"Automatic":[0],"segmentation":[1,45,65],"of":[2,46,68,74,96,134,141,166,172],"histological":[3],"images":[4],"is":[5,84,90,128],"an":[6,54],"important":[7],"step":[8,57,66],"for":[9,25,43,81],"increasing":[10],"throughput":[11],"while":[12],"maintaining":[13],"high":[14],"accuracy,":[15],"avoiding":[16],"variation":[17],"from":[18],"subjective":[19],"bias,":[20],"and":[21,32,61,71,149,170,174],"reducing":[22],"the":[23,64,82,85,94,97,100,111,125,161],"costs":[24],"diagnosing":[26],"human":[27],"illnesses":[28],"such":[29],"as":[30],"cancer":[31],"Alzheimer's":[33],"disease.":[34],"In":[35],"this":[36],"paper,":[37],"we":[38],"present":[39],"a":[40,72,117,131,138],"novel":[41],"method":[42,83,102],"unsupervised":[44],"cell":[47,123],"nuclei":[48],"in":[49,164],"stained":[50],"histology":[51],"tissue.":[52],"Following":[53],"initial":[55],"preprocessing":[56],"involving":[58],"color":[59],"deconvolution":[60],"image":[62],"reconstruction,":[63],"consists":[67],"multilevel":[69],"thresholding":[70],"series":[73],"morphological":[75],"operations.":[76],"The":[77],"only":[78],"parameter":[79,108],"required":[80],"minimum":[86],"region":[87],"size,":[88],"which":[89],"set":[91],"according":[92],"to":[93,122],"resolution":[95],"image.":[98],"Hence,":[99],"proposed":[101],"requires":[103,113],"no":[104,114],"training":[105],"sets":[106],"or":[107,116],"learning.":[109],"Because":[110],"algorithm":[112],"assumptions":[115],"priori":[118],"information":[119],"with":[120,168],"regard":[121],"morphology,":[124],"automatic":[126],"approach":[127],"generalizable":[129],"across":[130,137],"wide":[132],"range":[133],"tissues.":[135],"Evaluation":[136],"dataset":[139,163],"consisting":[140],"diverse":[142],"tissues,":[143],"including":[144],"breast,":[145],"liver,":[146],"gastric":[147],"mucosa":[148],"bone":[150],"marrow,":[151],"shows":[152],"superior":[153],"performance":[154],"over":[155],"four":[156],"other":[157],"recent":[158],"methods":[159],"on":[160],"same":[162],"terms":[165],"F-measure":[167],"precision":[169],"recall":[171],"0.929":[173],"0.886,":[175],"respectively.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}