{"id":"https://openalex.org/W7128364711","doi":"https://doi.org/10.1145/3787120.3787124","title":"Enhancing Morphological Discrimination in Red Blood Cell Images via Multi-Level Attention","display_name":"Enhancing Morphological Discrimination in Red Blood Cell Images via Multi-Level Attention","publication_year":2025,"publication_date":"2025-12-04","ids":{"openalex":"https://openalex.org/W7128364711","doi":"https://doi.org/10.1145/3787120.3787124"},"language":null,"primary_location":{"id":"doi:10.1145/3787120.3787124","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3787120.3787124","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 5th International Conference on Artificial Intelligence and Application Technologies","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3787120.3787124","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066828397","display_name":"Yidong Cao","orcid":"https://orcid.org/0009-0009-3119-8287"},"institutions":[{"id":"https://openalex.org/I42766147","display_name":"University of Toyama","ror":"https://ror.org/0445phv87","country_code":"JP","type":"education","lineage":["https://openalex.org/I42766147"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yidong Cao","raw_affiliation_strings":["University of Toyama, Toyama, Japan"],"raw_orcid":"https://orcid.org/0009-0009-3119-8287","affiliations":[{"raw_affiliation_string":"University of Toyama, Toyama, Japan","institution_ids":["https://openalex.org/I42766147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125376255","display_name":"Zhipeng Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I42766147","display_name":"University of Toyama","ror":"https://ror.org/0445phv87","country_code":"JP","type":"education","lineage":["https://openalex.org/I42766147"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zhipeng Liu","raw_affiliation_strings":["University of Toyama, Toyama, Japan"],"raw_orcid":"https://orcid.org/0009-0002-8541-9136","affiliations":[{"raw_affiliation_string":"University of Toyama, Toyama, Japan","institution_ids":["https://openalex.org/I42766147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123524682","display_name":"Haozhe Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I42766147","display_name":"University of Toyama","ror":"https://ror.org/0445phv87","country_code":"JP","type":"education","lineage":["https://openalex.org/I42766147"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Haozhe Liu","raw_affiliation_strings":["University of Toyama, Toyama, Japan"],"raw_orcid":"https://orcid.org/0009-0009-2486-2629","affiliations":[{"raw_affiliation_string":"University of Toyama, Toyama, Japan","institution_ids":["https://openalex.org/I42766147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125409987","display_name":"Chuantong Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I42766147","display_name":"University of Toyama","ror":"https://ror.org/0445phv87","country_code":"JP","type":"education","lineage":["https://openalex.org/I42766147"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chuantong Zhang","raw_affiliation_strings":["University of Toyama, Toyama, Japan"],"raw_orcid":"https://orcid.org/0009-0002-4802-5074","affiliations":[{"raw_affiliation_string":"University of Toyama, Toyama, Japan","institution_ids":["https://openalex.org/I42766147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125424283","display_name":"Yu Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I42766147","display_name":"University of Toyama","ror":"https://ror.org/0445phv87","country_code":"JP","type":"education","lineage":["https://openalex.org/I42766147"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yu Gao","raw_affiliation_strings":["University of Toyama, Toyama, Japan"],"raw_orcid":"https://orcid.org/0009-0009-6545-3135","affiliations":[{"raw_affiliation_string":"University of Toyama, Toyama, Japan","institution_ids":["https://openalex.org/I42766147"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125388671","display_name":"Shangce Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I42766147","display_name":"University of Toyama","ror":"https://ror.org/0445phv87","country_code":"JP","type":"education","lineage":["https://openalex.org/I42766147"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shangce Gao","raw_affiliation_strings":["University of Toyama, Toyama, Japan"],"raw_orcid":"https://orcid.org/0000-0001-5042-3261","affiliations":[{"raw_affiliation_string":"University of Toyama, Toyama, Japan","institution_ids":["https://openalex.org/I42766147"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I42766147"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"22","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9907000064849854,"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":0.9907000064849854,"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/T10862","display_name":"AI in cancer detection","score":0.0024999999441206455,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.0008999999845400453,"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/discriminative-model","display_name":"Discriminative model","score":0.7688999772071838},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6814000010490417},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.66839998960495},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6152999997138977},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5565000176429749},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.536300003528595}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7688999772071838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7339000105857849},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6814000010490417},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.66839998960495},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6152999997138977},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5995000004768372},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5565000176429749},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.536300003528595},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3971000015735626},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3765000104904175},{"id":"https://openalex.org/C2776557347","wikidata":"https://www.wikidata.org/wiki/Q37187","display_name":"Red blood cell","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3294000029563904},{"id":"https://openalex.org/C2779979121","wikidata":"https://www.wikidata.org/wiki/Q211709","display_name":"Blood cell","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C189014844","wikidata":"https://www.wikidata.org/wiki/Q189118","display_name":"Cell type","level":3,"score":0.3019999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3787120.3787124","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3787120.3787124","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 5th International Conference on Artificial Intelligence and Application Technologies","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3787120.3787124","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3787120.3787124","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 5th International Conference on Artificial Intelligence and Application Technologies","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7572644948959351}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2752782242","https://openalex.org/W2884585870","https://openalex.org/W3034552520","https://openalex.org/W3119144467","https://openalex.org/W3177634011","https://openalex.org/W3196700921","https://openalex.org/W3199733685","https://openalex.org/W4304175695","https://openalex.org/W4387162923","https://openalex.org/W4391305635","https://openalex.org/W4391765461","https://openalex.org/W4399515534","https://openalex.org/W4402082386","https://openalex.org/W4404851440","https://openalex.org/W4404916048"],"related_works":[],"abstract_inverted_index":{"Reliable":[0],"red":[1,81],"blood":[2,82],"cell":[3,22,83],"classification":[4],"is":[5],"essential":[6],"for":[7,28,108],"facilitating":[8],"early":[9],"detection":[10],"and":[11,72],"treatment":[12],"of":[13],"hematological":[14],"diseases.":[15],"Nonetheless,":[16],"the":[17,91],"considerable":[18],"morphological":[19],"diversity":[20],"among":[21],"types":[23],"presents":[24],"a":[25,51,79,105],"major":[26],"challenge":[27],"traditional":[29],"convolutional":[30],"neural":[31],"networks.":[32],"In":[33],"response":[34],"to":[35],"this":[36],"issue,":[37],"we":[38],"introduce":[39],"MAFPN":[40,63,103],"(Multi-scale":[41],"Attention":[42],"Feature":[43],"Pyramid":[44],"Network),":[45],"an":[46],"attention-integrated":[47],"architecture":[48],"built":[49],"on":[50,78],"ResNet-based":[52],"FPN":[53,93],"framework.":[54],"By":[55],"embedding":[56],"attention":[57],"modules":[58],"at":[59],"multiple":[60],"hierarchical":[61],"levels,":[62],"effectively":[64],"enhances":[65],"feature":[66],"representations":[67],"by":[68],"emphasizing":[69],"discriminative":[70],"patterns":[71],"filtering":[73],"out":[74],"irrelevant":[75],"signals.":[76],"Evaluations":[77],"four-category":[80],"dataset":[84],"indicate":[85],"that":[86,102],"our":[87],"method":[88],"consistently":[89],"surpasses":[90],"baseline":[92],"across":[94],"various":[95],"standard":[96],"performance":[97],"metrics.":[98],"These":[99],"findings":[100],"suggest":[101],"constitutes":[104],"promising":[106],"solution":[107],"fine-grained":[109],"medical":[110],"image":[111],"classification,":[112],"leveraging":[113],"attention-guided":[114],"multi-scale":[115],"representation":[116],"learning.":[117]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-02-10T00:00:00"}
