{"id":"https://openalex.org/W4408280845","doi":"https://doi.org/10.1109/access.2025.3550004","title":"DeepCRC-Net: An Attention-Driven Deep Learning Network for Colorectal Cancer Classification Using Xception and Efficient Lightweight Local Feature Fusion Networks","display_name":"DeepCRC-Net: An Attention-Driven Deep Learning Network for Colorectal Cancer Classification Using Xception and Efficient Lightweight Local Feature Fusion Networks","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4408280845","doi":"https://doi.org/10.1109/access.2025.3550004"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3550004","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3550004","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3550004","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114227650","display_name":"Akshaj Singh Bisht","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Akshaj Singh Bisht","raw_affiliation_strings":["School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Chennai, India"],"raw_orcid":"https://orcid.org/0009-0003-9118-465X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Chennai, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111328695","display_name":"Armaano Ajay","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Armaano Ajay","raw_affiliation_strings":["School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Chennai, India"],"raw_orcid":"https://orcid.org/0009-0009-2752-1352","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Chennai, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101680456","display_name":"R. Karthik","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R. Karthik","raw_affiliation_strings":["Centre for Cyber Physical Systems (CCPS), Vellore Institute of Technology, Chennai, India"],"raw_orcid":"https://orcid.org/0000-0002-5250-4337","affiliations":[{"raw_affiliation_string":"Centre for Cyber Physical Systems (CCPS), Vellore Institute of Technology, Chennai, India","institution_ids":["https://openalex.org/I876193797"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5114227650"],"corresponding_institution_ids":["https://openalex.org/I876193797"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":13.9966,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.98501094,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"49362","last_page":"49374"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9958000183105469,"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":0.9958000183105469,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9617000222206116,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7494089603424072},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6859700083732605},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6480225324630737},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46658211946487427},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4441901445388794},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4353739619255066}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7494089603424072},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6859700083732605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6480225324630737},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46658211946487427},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4441901445388794},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4353739619255066},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3550004","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3550004","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5f55e84af8cc4f77829973c74605ef94","is_oa":true,"landing_page_url":"https://doaj.org/article/5f55e84af8cc4f77829973c74605ef94","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":"IEEE Access, Vol 13, Pp 49362-49374 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3550004","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3550004","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.5899999737739563}],"awards":[],"funders":[{"id":"https://openalex.org/F4320319346","display_name":"Vellore Institute of Technology, Chennai","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W2531409750","https://openalex.org/W2601564443","https://openalex.org/W2765811365","https://openalex.org/W2794803511","https://openalex.org/W2922509574","https://openalex.org/W2939884729","https://openalex.org/W2954678774","https://openalex.org/W2963125010","https://openalex.org/W2966039277","https://openalex.org/W2970602317","https://openalex.org/W2979695050","https://openalex.org/W2994908874","https://openalex.org/W3004016611","https://openalex.org/W3035414587","https://openalex.org/W3041133507","https://openalex.org/W3047530476","https://openalex.org/W3119205652","https://openalex.org/W3128268064","https://openalex.org/W3129469040","https://openalex.org/W3138501564","https://openalex.org/W3159875333","https://openalex.org/W3162418282","https://openalex.org/W3178723556","https://openalex.org/W3181227444","https://openalex.org/W3191409400","https://openalex.org/W3194841206","https://openalex.org/W3203862103","https://openalex.org/W4312112335","https://openalex.org/W4321201254","https://openalex.org/W4321793931","https://openalex.org/W4362637571","https://openalex.org/W4381550720","https://openalex.org/W4385878178","https://openalex.org/W4386625304","https://openalex.org/W4387933377","https://openalex.org/W4388459526","https://openalex.org/W4390079535","https://openalex.org/W4400908458","https://openalex.org/W4400912847"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W3086377361"],"abstract_inverted_index":{"Colorectal":[0],"cancer":[1],"(CRC)":[2],"is":[3,16,35],"one":[4],"of":[5,9,24,147,157,167,172],"the":[6,28,56,77,84,102,145,148,153,158,177],"primary":[7],"causes":[8],"cancer-related":[10],"deaths":[11],"globally,":[12],"and":[13,37,58,95,116,126,138,169,188],"early":[14],"detection":[15],"critical":[17],"for":[18,31],"improving":[19],"patient":[20],"outcomes.":[21],"Histopathological":[22],"analysis":[23,57],"colorectal":[25],"tissue":[26],"remains":[27],"gold":[29],"standard":[30],"diagnosis,":[32],"however":[33],"it":[34],"labour-intensive":[36],"prone":[38],"to":[39,45,71,87,123,150],"human":[40],"error":[41],"which":[42,109,143],"could":[43],"lead":[44],"misdiagnosis.":[46],"Deep":[47],"learning":[48],"models":[49],"offer":[50],"a":[51,66],"promising":[52],"solution":[53],"by":[54,184,191],"automating":[55],"enhancing":[59],"diagnostic":[60],"accuracy.":[61],"This":[62],"research":[63],"introduces":[64],"DeepCRC-Net,":[65],"novel":[67],"dual-track":[68],"architecture":[69],"designed":[70],"classify":[72],"CRC":[73,159],"histopathology":[74],"images":[75],"using":[76,91,140],"EBHI":[78,178],"dataset.":[79,179],"The":[80,98,130,161],"first":[81],"track":[82,100],"leverages":[83],"Xception":[85],"network":[86],"capture":[88,124],"long-range":[89],"dependencies":[90],"depth-wise":[92],"separable":[93],"convolutions":[94],"residual":[96],"connections.":[97],"second":[99],"employs":[101],"Efficient":[103,111],"Lightweight":[104],"Local":[105],"Feature-Fusion":[106],"Network":[107],"(ELLFFN),":[108],"integrates":[110],"Semi-Local":[112],"Attention":[113],"Convolution":[114,120],"(ESAC)":[115],"Dynamic":[117],"Deformed":[118],"Shuffle-Fusion":[119],"(DDSFC)":[121],"blocks":[122],"semi-local":[125],"local":[127],"features":[128,132],"efficiently.":[129],"extracted":[131],"from":[133],"both":[134],"tracks":[135],"are":[136],"concatenated":[137],"refined":[139],"Shuffle":[141],"Attention,":[142],"enhances":[144],"ability":[146],"model":[149,163],"focus":[151],"on":[152,176],"most":[154],"informative":[155],"regions":[156],"images.":[160],"proposed":[162],"achieved":[164],"an":[165,170],"accuracy":[166,187],"98.6%":[168],"F1-score":[171],"99.25%":[173],"when":[174],"tested":[175],"DeepCRC-Net":[180],"outperforms":[181],"existing":[182],"studies":[183],"2.5%":[185],"in":[186],"state-of-the-art":[189],"CNNs":[190],"4.2%.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6}],"updated_date":"2026-05-13T08:25:38.343686","created_date":"2025-10-10T00:00:00"}
