{"id":"https://openalex.org/W2440598369","doi":"https://doi.org/10.1109/isbi.2016.7493418","title":"Automatic nuclei and cytoplasm segmentation of leukocytes with color and texture-based image enhancement","display_name":"Automatic nuclei and cytoplasm segmentation of leukocytes with color and texture-based image enhancement","publication_year":2016,"publication_date":"2016-04-01","ids":{"openalex":"https://openalex.org/W2440598369","doi":"https://doi.org/10.1109/isbi.2016.7493418","mag":"2440598369"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2016.7493418","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2016.7493418","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","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/A5006903842","display_name":"Afaf Tareef","orcid":"https://orcid.org/0000-0001-7265-030X"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Afaf Tareef","raw_affiliation_strings":["School of Information Technologies, University of Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technologies, University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041567418","display_name":"Yang Song","orcid":"https://orcid.org/0000-0003-1283-1672"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yang Song","raw_affiliation_strings":["School of Information Technologies, University of Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technologies, University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076697411","display_name":"Weidong Cai","orcid":"https://orcid.org/0000-0003-3706-8896"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Weidong Cai","raw_affiliation_strings":["School of Information Technologies, University of Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technologies, University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112684346","display_name":"Yue Wang","orcid":"https://orcid.org/0009-0003-5310-2713"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue Wang","raw_affiliation_strings":["Bradley Department of Electrical and Computer Engineering, Virginia Tech, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bradley Department of Electrical and Computer Engineering, Virginia Tech, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068891693","display_name":"Dagan Feng","orcid":"https://orcid.org/0000-0002-3381-214X"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]},{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["AU","CN"],"is_corresponding":false,"raw_author_name":"Dagan D. Feng","raw_affiliation_strings":["Med-X Research Institute, Shanghai Jiaotong University, China","School of Information Technologies, University of Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Med-X Research Institute, Shanghai Jiaotong University, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"School of Information Technologies, University of Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101826256","display_name":"Mei Chen","orcid":"https://orcid.org/0000-0002-5309-136X"},"institutions":[{"id":"https://openalex.org/I113508548","display_name":"Albany State University","ror":"https://ror.org/01vme4277","country_code":"US","type":"education","lineage":["https://openalex.org/I113508548"]},{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]},{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mei Chen","raw_affiliation_strings":["Computer Engineering Department, University of Albany State University of New York, USA","Robotics Institute, Carnegie Mellon University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Engineering Department, University of Albany State University of New York, USA","institution_ids":["https://openalex.org/I113508548","https://openalex.org/I392282"]},{"raw_affiliation_string":"Robotics Institute, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"935","last_page":"938"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9998999834060669,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7489830851554871},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7151705026626587},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6299353241920471},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5941067934036255},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5763258934020996},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5594611763954163},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5517697334289551},{"id":"https://openalex.org/keywords/cytoplasm","display_name":"Cytoplasm","score":0.49930620193481445},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.47634604573249817},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.4275941848754883},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.38417163491249084},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2591215968132019},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.10318666696548462},{"id":"https://openalex.org/keywords/cell-biology","display_name":"Cell biology","score":0.0649445652961731}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7489830851554871},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7151705026626587},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6299353241920471},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5941067934036255},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5763258934020996},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5594611763954163},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5517697334289551},{"id":"https://openalex.org/C190062978","wikidata":"https://www.wikidata.org/wiki/Q79899","display_name":"Cytoplasm","level":2,"score":0.49930620193481445},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.47634604573249817},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4275941848754883},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.38417163491249084},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2591215968132019},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.10318666696548462},{"id":"https://openalex.org/C95444343","wikidata":"https://www.wikidata.org/wiki/Q7141","display_name":"Cell biology","level":1,"score":0.0649445652961731}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2016.7493418","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2016.7493418","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1086665","https://openalex.org/W1526147865","https://openalex.org/W1601107692","https://openalex.org/W1977598874","https://openalex.org/W1980276039","https://openalex.org/W2001412060","https://openalex.org/W2001737237","https://openalex.org/W2008840310","https://openalex.org/W2024723841","https://openalex.org/W2032673367","https://openalex.org/W2043424639","https://openalex.org/W2080860745","https://openalex.org/W2093075920","https://openalex.org/W2102699116","https://openalex.org/W2110218375","https://openalex.org/W2114926173","https://openalex.org/W2133059825","https://openalex.org/W2138960968","https://openalex.org/W2166098853","https://openalex.org/W2532163996","https://openalex.org/W2534622136","https://openalex.org/W6600052009","https://openalex.org/W6680096826"],"related_works":["https://openalex.org/W2138983844","https://openalex.org/W1968965685","https://openalex.org/W2012792772","https://openalex.org/W2356573839","https://openalex.org/W2111883783","https://openalex.org/W2009028679","https://openalex.org/W2357424838","https://openalex.org/W2356903262","https://openalex.org/W4237142086","https://openalex.org/W2327601824"],"abstract_inverted_index":{"Designing":[0],"a":[1,16,22,53],"single":[2],"automatic":[3],"and":[4,31,49,72,88,100,112,136],"accurate":[5,121],"segmentation":[6,25,140],"approach":[7,126],"for":[8],"different":[9],"classes":[10,36],"of":[11,33,37,132],"white":[12,38],"blood":[13,39,44,134],"cells":[14,40],"is":[15,57,94,127],"challenging":[17],"task.":[18],"This":[19],"paper":[20],"presents":[21],"fully":[23],"automated":[24],"framework":[26],"to":[27,65,96,118],"segment":[28],"both":[29],"nuclei":[30,68],"cytoplasm":[32,71,82,99],"five":[34],"major":[35],"in":[41],"the":[42,67,70,98,102,106,120],"peripheral":[43,133],"smears":[45],"based":[46,59,77,91],"on":[47,60,129],"color":[48,63],"texture":[50],"enhancement.":[51],"Particularly,":[52],"new":[54],"gray-scale":[55],"transform":[56,86],"generated":[58],"three":[61],"representative":[62],"channels":[64],"separate":[66],"from":[69],"background":[73],"by":[74],"Poisson":[75],"distribution":[76],"minimum":[78],"error":[79],"thresholding.":[80],"For":[81],"segmentation,":[83],"discrete":[84],"wavelet":[85],"(DWT)":[87],"morphological":[89],"filtering":[90,115],"enhancement":[92],"procedure":[93],"utilized":[95],"highlight":[97],"eliminate":[101],"small":[103],"details":[104],"inside":[105],"cells.":[107],"Finally":[108],"level":[109],"set-based":[110],"refinement":[111],"false":[113],"candidates":[114],"are":[116],"applied":[117],"obtain":[119],"cell":[122],"segmentation.":[123],"The":[124],"proposed":[125],"evaluated":[128],"two":[130],"sets":[131],"smears,":[135],"it":[137],"demonstrates":[138],"improved":[139],"performance":[141],"when":[142],"compared":[143],"with":[144],"existing":[145],"methods.":[146]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}