{"id":"https://openalex.org/W4378804556","doi":"https://doi.org/10.1145/3592686.3592705","title":"An atrium segmentation network with location guidance and siamese adjustment","display_name":"An atrium segmentation network with location guidance and siamese adjustment","publication_year":2023,"publication_date":"2023-02-10","ids":{"openalex":"https://openalex.org/W4378804556","doi":"https://doi.org/10.1145/3592686.3592705"},"language":"en","primary_location":{"id":"doi:10.1145/3592686.3592705","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3592686.3592705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 3rd International Conference on Bioinformatics and Intelligent Computing","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/A5059054469","display_name":"Yuhan Xie","orcid":"https://orcid.org/0009-0001-4616-6132"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuhan Xie","raw_affiliation_strings":["School of Electronics and Communication Engineering, Sun Yat-sen University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Sun Yat-sen University, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100352614","display_name":"Zhiyong Zhang","orcid":"https://orcid.org/0000-0003-0638-5434"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Zhang","raw_affiliation_strings":["School of Electronics and Communication Engineering, Sun Yat-sen University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Sun Yat-sen University, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035335266","display_name":"Shao\u2010Long Chen","orcid":"https://orcid.org/0000-0003-4619-2602"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaolong Chen","raw_affiliation_strings":["School of Electronics and Communication Engineering, Sun Yat-sen University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Sun Yat-sen University, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051522890","display_name":"Changzhen Qiu","orcid":"https://orcid.org/0000-0003-4649-1178"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changzhen Qiu","raw_affiliation_strings":["School of Electronics and Communication Engineering, Sun Yat-sen University, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering, Sun Yat-sen University, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5059054469"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.2271,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55731256,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"98","last_page":"104"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10172","display_name":"Cardiac Valve Diseases and Treatments","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10172","display_name":"Cardiac Valve Diseases and Treatments","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9878000020980835,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9868000149726868,"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/segmentation","display_name":"Segmentation","score":0.8702763915061951},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.70423424243927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6878005862236023},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6429293751716614},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6031662225723267},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5346713662147522},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4773392975330353},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.477178692817688},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4713325500488281},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41836339235305786},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10892036557197571},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08300957083702087}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8702763915061951},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.70423424243927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6878005862236023},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6429293751716614},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6031662225723267},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5346713662147522},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4773392975330353},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.477178692817688},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4713325500488281},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41836339235305786},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10892036557197571},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08300957083702087},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3592686.3592705","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3592686.3592705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 3rd International Conference on Bioinformatics and Intelligent Computing","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":16,"referenced_works":["https://openalex.org/W1492293293","https://openalex.org/W1901129140","https://openalex.org/W1985263919","https://openalex.org/W1994062553","https://openalex.org/W2083775921","https://openalex.org/W2104276184","https://openalex.org/W2804047627","https://openalex.org/W2897451575","https://openalex.org/W2954680583","https://openalex.org/W2974784700","https://openalex.org/W2996290406","https://openalex.org/W3007268491","https://openalex.org/W3015788359","https://openalex.org/W3093394156","https://openalex.org/W3095207884","https://openalex.org/W3194417301"],"related_works":["https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W3011384228","https://openalex.org/W4313052709","https://openalex.org/W3199300986","https://openalex.org/W2945274617","https://openalex.org/W4298131179","https://openalex.org/W2375430703","https://openalex.org/W4323893507"],"abstract_inverted_index":{"The":[0,86,109],"segmentation":[1,25,58,107,121,143,160],"of":[2,7,14,22,42,48,72,95,104,127,162,170],"atrial":[3,84],"scan":[4],"images":[5,35,44,73],"is":[6],"great":[8],"significance":[9],"for":[10],"the":[11,15,18,23,39,46,92,96,101,105,115,120,124],"three-dimensional":[12],"reconstruction":[13],"atrium":[16,57,125],"and":[17,31,45,64,76,129,165],"surgical":[19],"positioning.":[20],"Most":[21],"existing":[24],"networks":[26],"adopt":[27],"a":[28],"2D":[29,142],"structure":[30],"only":[32],"take":[33],"original":[34],"as":[36,74,156],"input,":[37],"ignoring":[38],"context":[40,116],"information":[41,94,117],"3D":[43],"role":[47],"prior":[49,93],"information.":[50],"In":[51],"this":[52],"paper,":[53],"we":[54,158],"propose":[55],"an":[56,78],"network":[59],"LGSANet":[60],"with":[61,154],"location":[62,87],"guidance":[63,88],"siamese":[65,110],"adjustment,":[66],"which":[67],"takes":[68],"adjacent":[69],"three":[70],"slices":[71],"input":[75],"adopts":[77],"end-to-end":[79],"approach":[80],"to":[81,99,118,139],"achieve":[82],"coarse-to-fine":[83],"segmentation.":[85],"(LG)":[89],"block":[90,113],"uses":[91,114],"localization":[97],"map":[98],"guide":[100],"encoding":[102],"features":[103],"fine":[106],"stage.":[108],"adjustment":[111],"(SA)":[112],"adjust":[119],"edges.":[122],"On":[123],"datasets":[126],"ACDC":[128,171],"ASC,":[130],"sufficient":[131],"experiments":[132],"prove":[133],"that":[134,146],"our":[135],"method":[136],"can":[137,148],"adapt":[138],"many":[140],"classic":[141],"networks,":[144],"so":[145],"it":[147],"obtain":[149],"significant":[150],"performance":[151],"improvements.":[152],"Specifically,":[153],"UNet":[155],"backbone,":[157],"reach":[159],"improvements":[161],"1.98%,":[163],"2.32%":[164],"2.37%":[166],"on":[167],"different":[168],"organs":[169],"dataset.":[172]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}