{"id":"https://openalex.org/W4405271118","doi":"https://doi.org/10.1109/cvmi61877.2024.10781544","title":"Enhanced Fetal Ultrasound Image Segmentation using Spatial Attention Mechanisms with UNet: SAUnet","display_name":"Enhanced Fetal Ultrasound Image Segmentation using Spatial Attention Mechanisms with UNet: SAUnet","publication_year":2024,"publication_date":"2024-10-19","ids":{"openalex":"https://openalex.org/W4405271118","doi":"https://doi.org/10.1109/cvmi61877.2024.10781544"},"language":"en","primary_location":{"id":"doi:10.1109/cvmi61877.2024.10781544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvmi61877.2024.10781544","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Computer Vision and Machine Intelligence (CVMI)","raw_type":"proceedings-article"},"type":"article","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/A5066954621","display_name":"Harshita Verma","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Harshita Verma","raw_affiliation_strings":["Rajkiya Engineering College,Dept. of Computer Science and Engineering,Kannauj,India"],"affiliations":[{"raw_affiliation_string":"Rajkiya Engineering College,Dept. of Computer Science and Engineering,Kannauj,India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079794723","display_name":"Bdk Patro","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bdk Patro","raw_affiliation_strings":["Rajkiya Engineering College,Dept. of Computer Science and Engineering,Kannauj,India"],"affiliations":[{"raw_affiliation_string":"Rajkiya Engineering College,Dept. of Computer Science and Engineering,Kannauj,India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5066954621"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5236,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68214792,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.921999990940094,"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/T11448","display_name":"Face recognition and analysis","score":0.921999990940094,"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/T13693","display_name":"Smart Systems and Machine Learning","score":0.9064000248908997,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/computer-science","display_name":"Computer science","score":0.6459011435508728},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6179243326187134},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6027858853340149},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5655161738395691},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5181295275688171},{"id":"https://openalex.org/keywords/ultrasound","display_name":"Ultrasound","score":0.4930262267589569},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.16392052173614502},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.14775729179382324}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6459011435508728},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6179243326187134},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6027858853340149},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5655161738395691},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5181295275688171},{"id":"https://openalex.org/C143753070","wikidata":"https://www.wikidata.org/wiki/Q162564","display_name":"Ultrasound","level":2,"score":0.4930262267589569},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.16392052173614502},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.14775729179382324}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvmi61877.2024.10781544","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvmi61877.2024.10781544","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Computer Vision and Machine Intelligence (CVMI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2888303187","https://openalex.org/W2943449916","https://openalex.org/W2958612150","https://openalex.org/W2979459070","https://openalex.org/W3003833709","https://openalex.org/W3013799281","https://openalex.org/W3022941278","https://openalex.org/W3088355951","https://openalex.org/W3124211545","https://openalex.org/W3157636025","https://openalex.org/W3161081823","https://openalex.org/W3165920082","https://openalex.org/W3181880044","https://openalex.org/W3194519097","https://openalex.org/W3213184550","https://openalex.org/W3217042496","https://openalex.org/W4206735871","https://openalex.org/W4212936569","https://openalex.org/W4224140474","https://openalex.org/W4387490528","https://openalex.org/W7006558171"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Fetal":[0],"Ultrasound":[1],"(US)":[2],"imaging":[3,190],"is":[4,23],"necessary":[5],"to":[6,30,85],"prenatal":[7,189],"treatment,":[8],"as":[9,184],"it":[10],"provides":[11],"information":[12],"on":[13,74,95],"the":[14,19,31,53,71,78,96],"health":[15],"and":[16,89,114,131,139,167],"development":[17],"of":[18,105,120,149],"fetus.":[20],"Accurate":[21],"segmenting":[22],"essential":[24],"but":[25],"poses":[26],"significant":[27,157],"challenges":[28],"due":[29],"dynamic":[32],"fetal":[33,160],"anatomy.":[34],"This":[35,81],"paper":[36],"proposes":[37],"Unet":[38,54,153],"with":[39],"Spatial":[40],"Attention":[41],"(SAUnet),":[42],"a":[43,101,115,156,165,185],"novel":[44],"deep":[45],"learning":[46],"architecture":[47,154],"that":[48],"integrates":[49],"attention":[50,151],"mechanisms":[51],"into":[52],"framework.":[55],"Unlike":[56],"traditional":[57],"models,":[58],"SAUnet":[59],"dynamically":[60],"emphasizes":[61],"key":[62],"anatomical":[63],"structures":[64],"while":[65],"suppressing":[66],"irrelevant":[67],"background":[68],"information,":[69],"enhancing":[70],"model\u2019s":[72],"focus":[73],"informative":[75],"regions":[76],"within":[77],"US":[79,161],"images.":[80],"targeted":[82],"approach":[83],"leads":[84],"improved":[86],"segmentation":[87,126],"accuracy":[88],"robustness.":[90],"Our":[91],"method":[92],"was":[93],"evaluated":[94],"HC18":[97],"Challenge":[98],"dataset,":[99],"achieving":[100],"mean":[102,116,129],"absolute":[103],"difference(\u00b1std)":[104],"2.23":[106],"\u00b1":[107,122,136,141],"2.41":[108],"mm":[109,138,143],"in":[110,152,159],"head":[111],"circumference":[112],"measure":[113],"Dice":[117],"similarity":[118],"coefficient":[119],"97.63":[121],"1.85%,":[123],"demonstrating":[124],"high":[125],"accuracy.":[127],"Additionally,":[128],"difference":[130],"Hausdorff":[132],"distance":[133],"are":[134],"1.06":[135],"3.11":[137],"1.42":[140],"0.93":[142],"respectively":[144],"suggesting":[145],"robust":[146],"performance.":[147],"Incorporation":[148],"spatial":[150],"marks":[155],"advancement":[158],"image":[162],"segmentation,":[163],"offering":[164],"lightweight":[166],"efficient":[168],"model":[169],"suitable":[170],"for":[171,188],"real-time":[172],"clinical":[173],"deployment.":[174],"Benchmark":[175],"comparisons":[176],"highlight":[177],"SAUnet\u2019s":[178],"competitive":[179],"performance,":[180],"reinforcing":[181],"its":[182],"potential":[183],"state-of-the-art":[186],"solution":[187],"tasks.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
