{"id":"https://openalex.org/W4416250079","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229365","title":"DECSEFE-Org: a hierarchical AI-based framework for automatic DEtection, Classification, SEgmentation, and Feature Extraction of Organoids","display_name":"DECSEFE-Org: a hierarchical AI-based framework for automatic DEtection, Classification, SEgmentation, and Feature Extraction of Organoids","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250079","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229365"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11229365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229365","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5031565940","display_name":"Giovanni Cicceri","orcid":"https://orcid.org/0000-0002-1498-2215"},"institutions":[{"id":"https://openalex.org/I900890020","display_name":"University of Palermo","ror":"https://ror.org/044k9ta02","country_code":"IT","type":"education","lineage":["https://openalex.org/I900890020"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giovanni Cicceri","raw_affiliation_strings":["University of Palermo,BiND Department,Palermo,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Palermo,BiND Department,Palermo,Italy","institution_ids":["https://openalex.org/I900890020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065288854","display_name":"Carmelo Militello","orcid":"https://orcid.org/0000-0003-2249-9538"},"institutions":[{"id":"https://openalex.org/I4210155236","display_name":"National Research Council","ror":"https://ror.org/04zaypm56","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Carmelo Militello","raw_affiliation_strings":["Italian National Research Council,ICAR-CNR,Palermo,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Italian National Research Council,ICAR-CNR,Palermo,Italy","institution_ids":["https://openalex.org/I4210155236"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016477001","display_name":"Salvatore Vitabile","orcid":"https://orcid.org/0000-0002-2673-8551"},"institutions":[{"id":"https://openalex.org/I900890020","display_name":"University of Palermo","ror":"https://ror.org/044k9ta02","country_code":"IT","type":"education","lineage":["https://openalex.org/I900890020"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Salvatore Vitabile","raw_affiliation_strings":["University of Palermo,BiND Department,Palermo,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Palermo,BiND Department,Palermo,Italy","institution_ids":["https://openalex.org/I900890020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.2777000069618225,"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":0.2777000069618225,"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/T10336","display_name":"Cancer Cells and Metastasis","score":0.24279999732971191,"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"}},{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.19670000672340393,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/organoid","display_name":"Organoid","score":0.8532999753952026},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7081999778747559},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.6389999985694885},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6238999962806702},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5950999855995178},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5295000076293945},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5073999762535095}],"concepts":[{"id":"https://openalex.org/C31695470","wikidata":"https://www.wikidata.org/wiki/Q11293125","display_name":"Organoid","level":2,"score":0.8532999753952026},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7649999856948853},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7081999778747559},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.6389999985694885},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6238999962806702},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5950999855995178},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5848000049591064},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5295000076293945},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5073999762535095},{"id":"https://openalex.org/C32220436","wikidata":"https://www.wikidata.org/wiki/Q2072214","display_name":"Personalized medicine","level":2,"score":0.46459999680519104},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.40299999713897705},{"id":"https://openalex.org/C163763905","wikidata":"https://www.wikidata.org/wiki/Q17075943","display_name":"Precision medicine","level":2,"score":0.396699994802475},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38449999690055847},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3569999933242798},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31040000915527344},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2897000014781952},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2728999853134155}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11229365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229365","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":25,"referenced_works":["https://openalex.org/W2099540110","https://openalex.org/W2945472816","https://openalex.org/W2952481429","https://openalex.org/W2970873947","https://openalex.org/W2975634117","https://openalex.org/W3035353528","https://openalex.org/W3094621838","https://openalex.org/W3131221939","https://openalex.org/W3196897371","https://openalex.org/W3197097711","https://openalex.org/W4286462293","https://openalex.org/W4321374203","https://openalex.org/W4382602821","https://openalex.org/W4385376528","https://openalex.org/W4385489859","https://openalex.org/W4386076325","https://openalex.org/W4386807703","https://openalex.org/W4390743764","https://openalex.org/W4392203599","https://openalex.org/W4399248742","https://openalex.org/W4400619066","https://openalex.org/W4402709361","https://openalex.org/W4406260568","https://openalex.org/W4407415703","https://openalex.org/W4409222877"],"related_works":[],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"the":[3,10,48,59,68,180,190,212],"emergence":[4],"of":[5,12,50,71,184,219],"organoid-related":[6],"technology":[7],"has":[8],"transformed":[9],"landscape":[11],"biomedical":[13,222],"research":[14],"by":[15],"providing":[16],"near-physiological":[17],"models":[18,53,106],"that":[19,35,103],"closely":[20],"mimic":[21],"human":[22],"tissue.":[23],"Intestinal":[24],"organoids":[25,150,220],"are":[26],"three-dimensional":[27],"structures":[28],"derived":[29],"from":[30],"intestinal":[31,72],"stem":[32],"cells":[33],"state":[34],"offer":[36],"new":[37],"potential":[38],"for":[39,77,107,214],"disease":[40],"modeling,":[41],"drug":[42,171],"testing,":[43],"and":[44,62,87,100,114,127,152,158,174,182,203,208,216],"personalized":[45],"medicine.":[46],"However,":[47],"complexity":[49],"these":[51,92],"heterogeneous":[52],"requires":[54],"innovative":[55],"solutions":[56],"to":[57,84,123,135,169,193],"optimize":[58],"organoids\u2019":[60],"characterization":[61],"monitoring.":[63],"From":[64],"a":[65,98,147],"technological":[66],"perspective,":[67],"automated":[69,215],"analysis":[70,198,218],"organoid":[73,109],"images":[74],"is":[75,167],"essential":[76],"high-throughput":[78,209],"screening,":[79],"yet":[80],"remains":[81],"challenging":[82],"due":[83],"morphological":[85,125],"variability":[86],"imaging":[88],"conditions.":[89],"To":[90],"overcome":[91],"challenges,":[93],"this":[94],"work":[95],"proposes":[96],"DECSEFE-Org,":[97],"hierarchical":[99],"modular":[101],"framework":[102,143],"combines":[104],"AI-based":[105],"real-time":[108],"detection":[110,202],"(YOLOv7),":[111],"classification":[112,157],"(DenseNet169),":[113],"segmentation":[115],"(SAM).":[116],"The":[117,142],"pipeline":[118],"further":[119],"includes":[120],"feature":[121],"extraction":[122],"quantify":[124],"parameters":[126],"explainable":[128],"AI":[129],"(XAI)":[130],"modules":[131],"based":[132],"on":[133,146],"SHAP":[134],"support":[136],"biological":[137],"interpretation":[138],"in":[139,156,162,201,221],"decision-making":[140],"processes.":[141],"was":[144],"tested":[145],"publicly":[148],"labeled":[149],"dataset":[151],"achieved":[153],"86.5%":[154],"accuracy":[155,183],"0.92":[159],"Dice":[160],"score":[161],"segmentation.":[163],"By":[164],"using":[165],"DECSEFE-Org":[166],"possible":[168],"accelerate":[170],"response":[172],"studies":[173],"improve":[175],"treatment":[176],"efficacy":[177],"evaluation,":[178],"overcoming":[179],"speed":[181],"traditional":[185],"methods.":[186],"Experimental":[187],"validation":[188],"demonstrates":[189],"pipeline\u2019s":[191],"ability":[192],"provide":[194],"near-real-time":[195],"results,":[196],"scalable":[197,217],"with":[199],"low-latency":[200],"segmentation,":[204],"while":[205],"maintaining":[206],"interpretability":[207],"suitability,":[210],"opening":[211],"way":[213],"research.":[223]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}
