{"id":"https://openalex.org/W4416102868","doi":"https://doi.org/10.1016/j.ijin.2025.11.003","title":"Transformer based framework for nuclei segmentation and cell counting on microscopic images of multiple organs","display_name":"Transformer based framework for nuclei segmentation and cell counting on microscopic images of multiple organs","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416102868","doi":"https://doi.org/10.1016/j.ijin.2025.11.003"},"language":"en","primary_location":{"id":"doi:10.1016/j.ijin.2025.11.003","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ijin.2025.11.003","pdf_url":null,"source":{"id":"https://openalex.org/S4210202467","display_name":"International Journal of Intelligent Networks","issn_l":"2666-6030","issn":["2666-6030"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Networks","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1016/j.ijin.2025.11.003","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011659226","display_name":"S. P. Raghavendra","orcid":"https://orcid.org/0009-0007-2449-2539"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"H.P. Ramya Shree","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0007-2449-2539","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057913396","display_name":"Minavathi Minavathi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210154507","display_name":"Mandya Institute of Medical Sciences","ror":"https://ror.org/04wnsdv29","country_code":"IN","type":"education","lineage":["https://openalex.org/I286135121","https://openalex.org/I4210154507"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Minavathi","raw_affiliation_strings":["Department of Computer Science and Engineering, P E S College of Engineering, Mandya 571401, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, P E S College of Engineering, Mandya 571401, Karnataka, India","institution_ids":["https://openalex.org/I4210154507"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102373198","display_name":"Dinesh M.S.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M.S. Dinesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057913396"],"corresponding_institution_ids":["https://openalex.org/I4210154507"],"apc_list":{"value":800,"currency":"USD","value_usd":800},"apc_paid":{"value":800,"currency":"USD","value_usd":800},"fwci":3.5821,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.9381636,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"6","issue":null,"first_page":"283","last_page":"292"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9178000092506409,"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":0.9178000092506409,"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":0.03290000185370445,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.01730000041425228,"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/segmentation","display_name":"Segmentation","score":0.8216999769210815},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.558899998664856},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4936999976634979},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.49219998717308044},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4731999933719635},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46950000524520874},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4652000069618225}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8216999769210815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7397000193595886},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7289999723434448},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.558899998664856},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4936999976634979},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.49219998717308044},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4731999933719635},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46950000524520874},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4652000069618225},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4399000108242035},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43959999084472656},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43209999799728394},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.38830000162124634},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.35499998927116394},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.3287999927997589},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.ijin.2025.11.003","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ijin.2025.11.003","pdf_url":null,"source":{"id":"https://openalex.org/S4210202467","display_name":"International Journal of Intelligent Networks","issn_l":"2666-6030","issn":["2666-6030"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Networks","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:bfd2a3416a6142f5a0c0448a420330a7","is_oa":true,"landing_page_url":"https://doaj.org/article/bfd2a3416a6142f5a0c0448a420330a7","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":"International Journal of Intelligent Networks, Vol 6, Iss , Pp 283-292 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.ijin.2025.11.003","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ijin.2025.11.003","pdf_url":null,"source":{"id":"https://openalex.org/S4210202467","display_name":"International Journal of Intelligent Networks","issn_l":"2666-6030","issn":["2666-6030"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Networks","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1125523343","https://openalex.org/W1968615915","https://openalex.org/W1970120446","https://openalex.org/W2043034051","https://openalex.org/W2280351290","https://openalex.org/W2798643036","https://openalex.org/W2885343725","https://openalex.org/W2890567626","https://openalex.org/W2905810301","https://openalex.org/W2928133111","https://openalex.org/W2963881378","https://openalex.org/W2967694147","https://openalex.org/W2974825848","https://openalex.org/W2996290406","https://openalex.org/W3014974815","https://openalex.org/W3034144495","https://openalex.org/W3084995528","https://openalex.org/W3096947210","https://openalex.org/W3111521801","https://openalex.org/W3132111858","https://openalex.org/W4223974852","https://openalex.org/W4376127444","https://openalex.org/W4410616123"],"related_works":[],"abstract_inverted_index":{"Segmentation":[0],"of":[1,30,37,62,87,93,100,115,151,166],"cell":[2,12],"nuclei":[3,32,63,167],"in":[4,11,169],"microscopic":[5],"images":[6],"is":[7,23],"a":[8,55,84,122,159],"vital":[9],"task":[10],"counting,":[13],"essential":[14],"for":[15,103,162],"cancer":[16,19],"diagnosis":[17],"and":[18,40,70,79,89,117,135,145,155],"grading.":[20],"Also,":[21],"it":[22],"more":[24],"challenging":[25],"due":[26],"to":[27,58,127],"the":[28,35,60,73,98,110,129,164],"presence":[29],"overlapping":[31,137],"which":[33],"complicates":[34],"process":[36],"accurately":[38],"distinguishing":[39],"separating":[41],"individual":[42],"nuclei.":[43,138],"This":[44],"study":[45],"introduces":[46],"an":[47,90],"approach":[48],"that":[49],"combines":[50],"Transformer-based":[51],"encoder":[52],"integrated":[53],"with":[54,83,109],"U-Net":[56,116],"architecture":[57],"improve":[59],"accuracy":[61],"segmentation.":[64],"The":[65],"proposed":[66],"model":[67],"was":[68,125],"trained":[69],"validated":[71],"on":[72],"2018":[74],"Data":[75],"Science":[76],"Bowl":[77],"dataset":[78],"demonstrated":[80],"state-of-the-art":[81],"performance,":[82],"Dice-Similarity-Coefficient":[85],"(DSC)":[86],"92.6%":[88],"Intersection-over-Union":[91],"(IoU)":[92],"86.22%.":[94],"These":[95],"metrics":[96],"highlight":[97],"effectiveness":[99],"leveraging":[101],"Transformers":[102],"capturing":[104],"global":[105],"contextual":[106],"information,":[107],"combined":[108],"localized":[111],"feature":[112],"extraction":[113],"capability":[114],"enhancing":[118],"segmentation":[119,130,168],"accuracy.":[120],"Additionally,":[121],"post-processing":[123,156],"step":[124],"applied":[126],"refine":[128],"masks,":[131],"improving":[132],"boundary":[133],"delineation":[134],"resolving":[136],"However,":[139],"there":[140],"exists":[141],"several":[142],"CNN":[143],"models":[144],"deep":[146],"learning":[147],"models,":[148],"this":[149],"combination":[150],"advanced":[152],"architectural":[153],"design":[154],"techniques":[157],"establishes":[158],"reliable":[160],"framework":[161],"addressing":[163],"challenges":[165],"biomedical":[170],"imaging":[171],"applications.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-06-07T08:38:57.713557","created_date":"2025-11-11T00:00:00"}