{"id":"https://openalex.org/W4408011927","doi":"https://doi.org/10.1080/21681163.2025.2468436","title":"Multimodal image fusion for ich detection and classification using parallel Dl models","display_name":"Multimodal image fusion for ich detection and classification using parallel Dl models","publication_year":2025,"publication_date":"2025-02-27","ids":{"openalex":"https://openalex.org/W4408011927","doi":"https://doi.org/10.1080/21681163.2025.2468436"},"language":"en","primary_location":{"id":"doi:10.1080/21681163.2025.2468436","is_oa":true,"landing_page_url":"https://doi.org/10.1080/21681163.2025.2468436","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/21681163.2025.2468436?needAccess=true","source":{"id":"https://openalex.org/S2764763012","display_name":"Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization","issn_l":"2168-1163","issn":["2168-1163","2168-1171"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Methods in Biomechanics and Biomedical Engineering: Imaging &amp; Visualization","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/21681163.2025.2468436?needAccess=true","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Sri Sangepu Nagaraju","orcid":null},"institutions":[{"id":"https://openalex.org/I10874241","display_name":"Jawaharlal Nehru Technological University, Hyderabad","ror":"https://ror.org/002tchr49","country_code":"IN","type":"education","lineage":["https://openalex.org/I10874241"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Sri Sangepu Nagaraju","raw_affiliation_strings":["JNTU Hyderabad"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JNTU Hyderabad","institution_ids":["https://openalex.org/I10874241"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105884280","display_name":"S. Prince Mary","orcid":"https://orcid.org/0000-0002-6840-8921"},"institutions":[{"id":"https://openalex.org/I43814544","display_name":"Sathyabama Institute of Science and Technology","ror":"https://ror.org/01defpn95","country_code":"IN","type":"education","lineage":["https://openalex.org/I43814544"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"S. Prince Mary","raw_affiliation_strings":["Sathyabama University of Chennai India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sathyabama University of Chennai India","institution_ids":["https://openalex.org/I43814544"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014551477","display_name":"Vivek Chandra","orcid":"https://orcid.org/0000-0002-4047-015X"},"institutions":[{"id":"https://openalex.org/I8975392","display_name":"Osmania University","ror":"https://ror.org/030sjb889","country_code":"IN","type":"education","lineage":["https://openalex.org/I8975392"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"V. Pavani Chandra","raw_affiliation_strings":["St. Ann\u2019s Degree college Osmania University Hyderabad"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"St. Ann\u2019s Degree college Osmania University Hyderabad","institution_ids":["https://openalex.org/I8975392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033342913","display_name":"Nandam Gayatri","orcid":"https://orcid.org/0000-0001-5729-5573"},"institutions":[{"id":"https://openalex.org/I1330855593","display_name":"Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology","ror":"https://ror.org/05bc5bx80","country_code":"IN","type":"education","lineage":["https://openalex.org/I1330855593"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nandam Gayatri","raw_affiliation_strings":["Vel Tech Engineering College"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Vel Tech Engineering College","institution_ids":["https://openalex.org/I1330855593"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I10874241"],"apc_list":null,"apc_paid":null,"fwci":1.396,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82419941,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"13","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9473999738693237,"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/T10320","display_name":"Neural Networks and Applications","score":0.9473999738693237,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9128000140190125,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6416217088699341},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6101570129394531},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5076109170913696},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5036575198173523},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.48692309856414795},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47783684730529785},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4481132924556732}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6416217088699341},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6101570129394531},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5076109170913696},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5036575198173523},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.48692309856414795},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47783684730529785},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4481132924556732},{"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:10.1080/21681163.2025.2468436","is_oa":true,"landing_page_url":"https://doi.org/10.1080/21681163.2025.2468436","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/21681163.2025.2468436?needAccess=true","source":{"id":"https://openalex.org/S2764763012","display_name":"Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization","issn_l":"2168-1163","issn":["2168-1163","2168-1171"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Methods in Biomechanics and Biomedical Engineering: Imaging &amp; Visualization","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:860c507a6daf479e90c8aa6eed787832","is_oa":true,"landing_page_url":"https://doaj.org/article/860c507a6daf479e90c8aa6eed787832","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":"Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, Vol 13, Iss 1 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/21681163.2025.2468436","is_oa":true,"landing_page_url":"https://doi.org/10.1080/21681163.2025.2468436","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/21681163.2025.2468436?needAccess=true","source":{"id":"https://openalex.org/S2764763012","display_name":"Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization","issn_l":"2168-1163","issn":["2168-1163","2168-1171"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computer Methods in Biomechanics and Biomedical Engineering: Imaging &amp; Visualization","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W2537341889","https://openalex.org/W2725150524","https://openalex.org/W2885195348","https://openalex.org/W2947016132","https://openalex.org/W3000145527","https://openalex.org/W3081911348","https://openalex.org/W3102168028","https://openalex.org/W3118235341","https://openalex.org/W3122629112","https://openalex.org/W3123237299","https://openalex.org/W3156605119","https://openalex.org/W3157802181","https://openalex.org/W3192493130","https://openalex.org/W3205641095","https://openalex.org/W3213153722","https://openalex.org/W4205217883","https://openalex.org/W4210261121","https://openalex.org/W4213056919","https://openalex.org/W4214591778","https://openalex.org/W4287829537","https://openalex.org/W4298008566","https://openalex.org/W4307127914","https://openalex.org/W4307726656","https://openalex.org/W4309771862","https://openalex.org/W4312219098","https://openalex.org/W4319598202","https://openalex.org/W4319921239","https://openalex.org/W4322501497","https://openalex.org/W4322738911","https://openalex.org/W4366122000","https://openalex.org/W4383068788","https://openalex.org/W4383751390","https://openalex.org/W4385421970","https://openalex.org/W4386141231","https://openalex.org/W4386849590","https://openalex.org/W4393144657","https://openalex.org/W4399895005","https://openalex.org/W4403701132","https://openalex.org/W6774097426"],"related_works":["https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2370195708","https://openalex.org/W1490651872","https://openalex.org/W2139242969","https://openalex.org/W2284201331","https://openalex.org/W2095903272","https://openalex.org/W1989561795"],"abstract_inverted_index":{"Intracranial":[0],"haemorrhage":[1,180],"(ICH)":[2],"can":[3,29],"be":[4],"a":[5,37,74,84,98,153],"potential":[6],"consequence":[7],"of":[8,34,156],"traumatic":[9],"brain":[10],"injuries.":[11],"Single-modality":[12],"images":[13,35,177],"provide":[14],"limited":[15],"information":[16],"due":[17],"to":[18,136,148,164],"different":[19,32],"imaging":[20],"principles":[21],"and":[22,51,81,83,96,107,123,138,142],"organ":[23],"structures.":[24],"Multimodality":[25],"image":[26,62,104],"fusion":[27,47,63],"techniques":[28],"help":[30],"incorporate":[31],"types":[33],"into":[36],"single,":[38],"high-quality":[39],"image,":[40],"but":[41],"current":[42],"methods":[43],"face":[44],"challenges":[45],"like":[46],"artefacts,":[48],"complex":[49],"design,":[50],"high":[52,173],"computational":[53],"costs.":[54],"This":[55],"paper":[56],"introduces":[57],"an":[58,93],"innovative":[59],"multimodal":[60,77,140],"medical":[61],"method":[64,114],"using":[65],"parallel":[66,169],"Deep":[67],"Learning":[68],"(DL)":[69],"models.":[70],"The":[71,90,113,131,167],"research":[72],"uses":[73,97,115],"carefully":[75,162],"chosen":[76],"dataset,":[78],"including":[79],"CT":[80],"MRI,":[82],"novel":[85],"segmentation":[86],"algorithm":[87],"called":[88],"DFA-UNet.":[89],"model":[91],"employs":[92],"encoder-decoder":[94],"structure":[95],"DFA":[99],"attention":[100],"module":[101],"for":[102,120,128,152],"efficient":[103],"feature":[105,110],"extraction":[106],"easy":[108],"channel":[109],"weight":[111],"integration.":[112],"Graph":[116],"Neural":[117,125],"Networks":[118,126],"(GNNs)":[119],"spatial":[121],"features":[122],"Recurrent":[124],"(RNNs)":[127],"temporal":[129],"complexities.":[130],"architecture":[132,171],"starts":[133],"with":[134],"pre-processing":[135],"standardize":[137],"enhance":[139],"data,":[141],"simultaneous":[143],"DL":[144,170],"models":[145],"are":[146,161],"included":[147,163],"analyze":[149],"fused":[150],"input":[151],"comprehensive":[154],"understanding":[155],"ICH":[157],"patterns.":[158],"Attention":[159],"mechanisms":[160],"improve":[165],"accessibility.":[166],"proposed":[168],"demonstrates":[172],"efficiency":[174],"in":[175],"classifying":[176],"as":[178],"either":[179],"or":[181],"non-haemorrhage.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-14T06:11:07.267592","created_date":"2025-10-10T00:00:00"}
