{"id":"https://openalex.org/W7085644513","doi":"https://doi.org/10.1109/tmrb.2025.3617977","title":"Conditional Latent Diffusion Models for PLAX Echocardiographic Image Synthesis: A Geometric-Anatomical Guided Approach","display_name":"Conditional Latent Diffusion Models for PLAX Echocardiographic Image Synthesis: A Geometric-Anatomical Guided Approach","publication_year":2025,"publication_date":"2025-10-08","ids":{"openalex":"https://openalex.org/W7085644513","doi":"https://doi.org/10.1109/tmrb.2025.3617977"},"language":"en","primary_location":{"id":"doi:10.1109/tmrb.2025.3617977","doi":"https://doi.org/10.1109/tmrb.2025.3617977","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmrb.2025.3617977","pdf_url":null,"source":{"id":"https://openalex.org/S4210223690","display_name":"IEEE Transactions on Medical Robotics and Bionics","issn_l":"2576-3202","issn":["2576-3202"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","norway-1","poland-20","russia-white-list-2","vabb-shw"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Robotics and Bionics","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/11380/1401603","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093460739","display_name":"Angelo Lasala","orcid":"https://orcid.org/0000-0002-5042-0834","observed_orcids":["https://orcid.org/0000-0002-5042-0834"]},"institutions":[{"id":"https://openalex.org/I162290304","display_name":"Scuola Superiore Sant'Anna","ror":"https://ror.org/025602r80","country_code":"IT","type":"education","lineage":["https://openalex.org/I162290304"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Angelo Lasala","raw_affiliation_strings":["BioRobotics Institute and the Department of Excellence in Robotics and AI, Scuola Superiore Sant&#x2019;Anna, Pisa, Italy"],"raw_orcid":"https://orcid.org/0000-0002-5042-0834","affiliations":[{"raw_affiliation_string":"BioRobotics Institute and the Department of Excellence in Robotics and AI, Scuola Superiore Sant&#x2019;Anna, Pisa, Italy","institution_ids":["https://openalex.org/I162290304"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076591016","display_name":"Maria Chiara Fiorentino","orcid":"https://orcid.org/0000-0002-7397-803X","observed_orcids":["https://orcid.org/0000-0002-7397-803X"]},"institutions":[{"id":"https://openalex.org/I122534668","display_name":"Marche Polytechnic University","ror":"https://ror.org/00x69rs40","country_code":"IT","type":"education","lineage":["https://openalex.org/I122534668"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Maria Chiara Fiorentino","raw_affiliation_strings":["Department of Information Engineering, Universit&#x00E0; Politecnica delle Marche, Ancona, Italy"],"raw_orcid":"https://orcid.org/0000-0002-7397-803X","affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Universit&#x00E0; Politecnica delle Marche, Ancona, Italy","institution_ids":["https://openalex.org/I122534668"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055886310","display_name":"Andrea Bandini","orcid":"https://orcid.org/0000-0002-3509-2887","observed_orcids":["https://orcid.org/0000-0002-3509-2887"]},"institutions":[{"id":"https://openalex.org/I162290304","display_name":"Scuola Superiore Sant'Anna","ror":"https://ror.org/025602r80","country_code":"IT","type":"education","lineage":["https://openalex.org/I162290304"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrea Bandini","raw_affiliation_strings":["BioRobotics Institute, the Department of Excellence in Robotics and AI, and the Health Science Interdisciplinary Research Center, Scuola Superiore Sant&#x2019;Anna, Pisa, Italy"],"raw_orcid":"https://orcid.org/0000-0002-3509-2887","affiliations":[{"raw_affiliation_string":"BioRobotics Institute, the Department of Excellence in Robotics and AI, and the Health Science Interdisciplinary Research Center, Scuola Superiore Sant&#x2019;Anna, Pisa, Italy","institution_ids":["https://openalex.org/I162290304"]}]},{"author_position":"last","author":{"id":null,"display_name":"Sara Moccia","orcid":"https://orcid.org/0000-0002-4494-8907","observed_orcids":["https://orcid.org/0000-0002-4494-8907"]},"institutions":[{"id":"https://openalex.org/I39387349","display_name":"University of Chieti-Pescara","ror":"https://ror.org/00qjgza05","country_code":"IT","type":"education","lineage":["https://openalex.org/I39387349"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Sara Moccia","raw_affiliation_strings":["Department of Innovative Technologies in Medicine and Dentistry, Universit&#x00E0; degli Studi &#x201C;G. d&#x2019;Annunzio&#x201D; Chieti-Pescara, Chieti-Pescara, Italy"],"raw_orcid":"https://orcid.org/0000-0002-4494-8907","affiliations":[{"raw_affiliation_string":"Department of Innovative Technologies in Medicine and Dentistry, Universit&#x00E0; degli Studi &#x201C;G. d&#x2019;Annunzio&#x201D; Chieti-Pescara, Chieti-Pescara, Italy","institution_ids":["https://openalex.org/I39387349"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.362,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62920633,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":96},"biblio":{"volume":"8","issue":"1","first_page":"18","last_page":"29"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.5205000042915344,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.5205000042915344,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.3546999990940094,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.014600000344216824,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/parasternal-long-axis-view","display_name":"parasternal long-axis view","score":0.9079999923706055},{"id":"https://openalex.org/keywords/echocardiography","display_name":"echocardiography","score":0.7979999780654907},{"id":"https://openalex.org/keywords/image-generation","display_name":"image generation","score":0.8870000243186951},{"id":"https://openalex.org/keywords/anatomical-priors","display_name":"anatomical priors","score":0.7799999713897705},{"id":"https://openalex.org/keywords/ventricular-hypertrophy","display_name":"ventricular hypertrophy","score":0.6890000104904175},{"id":"https://openalex.org/keywords/data-augmentation","display_name":"data augmentation","score":0.6349999904632568}],"concepts":[{"id":"https://openalex.org/C186738849","wikidata":"https://www.wikidata.org/wiki/Q12408","display_name":"Calipers","level":2,"score":0.8079000115394592},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.616599977016449},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5206000208854675},{"id":"https://openalex.org/C2776127602","wikidata":"https://www.wikidata.org/wiki/Q5038319","display_name":"Cardiac imaging","level":2,"score":0.5156999826431274},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4916999936103821},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.448199987411499},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4350999891757965},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.41280001401901245},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38109999895095825},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3635999858379364},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.3337000012397766},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.31610000133514404},{"id":"https://openalex.org/C23036609","wikidata":"https://www.wikidata.org/wiki/Q7136027","display_name":"Parasternal line","level":2,"score":0.29989999532699585},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.2964000105857849},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.2784999907016754},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2685000002384186},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tmrb.2025.3617977","doi":"https://doi.org/10.1109/tmrb.2025.3617977","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmrb.2025.3617977","pdf_url":null,"source":{"id":"https://openalex.org/S4210223690","display_name":"IEEE Transactions on Medical Robotics and Bionics","issn_l":"2576-3202","issn":["2576-3202"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","norway-1","poland-20","russia-white-list-2","vabb-shw"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Robotics and Bionics","raw_type":"journal-article"},{"id":"pmh:oai:iris.unimore.it:11380/1401603","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/11380/1401603","pdf_url":null,"source":{"id":"https://openalex.org/S4306400718","display_name":"IRIS UNIMORE (University of Modena and Reggio Emilia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I122346577","host_organization_name":"University of Modena and Reggio Emilia","host_organization_lineage":["https://openalex.org/I122346577"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:iris.unimore.it:11380/1401603","doi":null,"is_oa":true,"landing_page_url":"https://hdl.handle.net/11380/1401603","pdf_url":null,"source":{"id":"https://openalex.org/S4306400718","display_name":"IRIS UNIMORE (University of Modena and Reggio Emilia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I122346577","host_organization_name":"University of Modena and Reggio Emilia","host_organization_lineage":["https://openalex.org/I122346577"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.7246000170707703,"display_name":"Good health and well-being"}],"sustainable_development_goals_aurora":[{"id":"https://metadata.un.org/sdg/13","score":0.7669962644577026,"display_name":"Climate action"}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321873","display_name":"Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca","ror":"https://ror.org/0166hxq48"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1992343541","https://openalex.org/W1995934832","https://openalex.org/W2097618980","https://openalex.org/W2124624517","https://openalex.org/W2518965973","https://openalex.org/W2552465644","https://openalex.org/W2754156725","https://openalex.org/W2915232829","https://openalex.org/W2925288829","https://openalex.org/W2962785568","https://openalex.org/W2969640942","https://openalex.org/W2979321201","https://openalex.org/W3013692475","https://openalex.org/W3034399482","https://openalex.org/W3046143986","https://openalex.org/W3143299112","https://openalex.org/W3161539386","https://openalex.org/W3164581645","https://openalex.org/W3173964191","https://openalex.org/W3174416962","https://openalex.org/W3212514729","https://openalex.org/W4296960568","https://openalex.org/W4312933868","https://openalex.org/W4321380813","https://openalex.org/W4324142567","https://openalex.org/W4377695098","https://openalex.org/W4385272245","https://openalex.org/W4386071957","https://openalex.org/W4387211386","https://openalex.org/W4387225014","https://openalex.org/W4389739249","https://openalex.org/W4390872297","https://openalex.org/W4391594085","https://openalex.org/W4391884035","https://openalex.org/W4392903175","https://openalex.org/W4393154023","https://openalex.org/W4396215619","https://openalex.org/W4399067019","https://openalex.org/W4403069858","https://openalex.org/W4403070045","https://openalex.org/W4403211972","https://openalex.org/W4408100541","https://openalex.org/W4410204823"],"related_works":[],"abstract_inverted_index":{"Echocardiography":[0],"is":[1],"essential":[2],"in":[3,169],"cardiology,":[4],"with":[5,59,107,190],"the":[6,35,64,112,140,158,182],"parasternal":[7],"long":[8],"axis":[9],"(PLAX)":[10],"view":[11],"key":[12],"to":[13,52,80,125],"evaluating":[14],"cardiac":[15,23,108],"geometry":[16],"and":[17,27,56,131,147,176,186],"diagnosing":[18],"ventricular":[19,25],"hypertrophy.":[20],"Measurements":[21],"of":[22,46,67,119,160],"structures\u2014including":[24],"dimensions":[26],"wall":[28],"thickness,":[29],"obtained":[30],"by":[31,39,63,84,99],"placing":[32],"calipers":[33],"on":[34],"walls\u2014are":[36],"often":[37],"influenced":[38],"significant":[40],"inter-and":[41],"intra-clinician":[42],"variability.":[43],"The":[44],"design":[45],"automated":[47],"deep":[48],"learning":[49],"(DL)":[50],"algorithms":[51],"address":[53,72],"this":[54,73,179],"issue":[55],"support":[57],"clinician":[58],"measurements":[60],"remains":[61],"constrained":[62],"limited":[65],"availability":[66],"annotated":[68],"echocardiographic":[69,188],"datasets.":[70,172],"To":[71],"limitation,":[74],"we":[75],"propose":[76],"a":[77,116],"novel":[78],"method":[79,114,135],"synthesize":[81],"PLAX":[82],"images":[83,153],"using":[85,122],"spatial":[86],"information":[87],"from":[88,154],"caliper":[89,164],"positions.":[90],"Our":[91,134],"approach":[92,180],"uses":[93],"conditional":[94],"latent":[95],"diffusion":[96],"models,":[97],"guided":[98],"geometric-anatomical":[100],"priors":[101],"encoded":[102],"through":[103,115],"heatmap,":[104],"ensuring":[105],"alignment":[106],"anatomy.":[109],"We":[110],"evaluate":[111],"proposed":[113],"comprehensive":[117],"comparison":[118],"conditioning":[120],"strategies":[121],"specific":[123],"metrics":[124],"quantify":[126],"anatomical":[127,148],"agreement":[128],"between":[129],"synthetic":[130],"real":[132],"images.":[133],"shows":[136],"superior":[137],"performance,":[138],"achieving":[139],"best":[141],"image":[142],"quality":[143],"(Frechet":[144],"Inception":[145],"Distance:21.08)":[146],"consistency":[149],"(Davies-Bouldin":[150],"score:22.97).":[151],"Synthetic":[152],"our":[155],"model":[156],"enhanced":[157],"performance":[159],"DL":[161],"models":[162],"for":[163,184,193],"identification,":[165],"showing":[166],"their":[167],"value":[168],"augmenting":[170],"training":[171],"By":[173],"addressing":[174],"variability":[175],"standardizing":[177],"measurements,":[178],"paves":[181],"way":[183],"objective":[185],"reliable":[187],"analysis,":[189],"promising":[191],"implications":[192],"medical":[194],"imaging":[195],"analysis.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2025-10-10T00:00:00"}
