{"id":"https://openalex.org/W4408354262","doi":"https://doi.org/10.1109/icassp49660.2025.10888253","title":"Deep Sylvester Posterior Inference for Adaptive Compressed Sensing in Ultrasound Imaging","display_name":"Deep Sylvester Posterior Inference for Adaptive Compressed Sensing in Ultrasound Imaging","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408354262","doi":"https://doi.org/10.1109/icassp49660.2025.10888253"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10888253","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888253","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5115817529","display_name":"Simon W. Penninga","orcid":null},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Simon W. Penninga","raw_affiliation_strings":["Eindhoven University of Technology,Department of Electrical Engineering,Eindhoven,The Netherlands"],"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology,Department of Electrical Engineering,Eindhoven,The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003543657","display_name":"Hans van Gorp","orcid":"https://orcid.org/0000-0003-4823-2874"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Hans van Gorp","raw_affiliation_strings":["Eindhoven University of Technology,Department of Electrical Engineering,Eindhoven,The Netherlands"],"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology,Department of Electrical Engineering,Eindhoven,The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042985821","display_name":"Ruud J. G. van Sloun","orcid":"https://orcid.org/0000-0003-2845-0495"},"institutions":[{"id":"https://openalex.org/I83019370","display_name":"Eindhoven University of Technology","ror":"https://ror.org/02c2kyt77","country_code":"NL","type":"education","lineage":["https://openalex.org/I83019370"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ruud J.G. van Sloun","raw_affiliation_strings":["Eindhoven University of Technology,Department of Electrical Engineering,Eindhoven,The Netherlands"],"affiliations":[{"raw_affiliation_string":"Eindhoven University of Technology,Department of Electrical Engineering,Eindhoven,The Netherlands","institution_ids":["https://openalex.org/I83019370"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5115817529"],"corresponding_institution_ids":["https://openalex.org/I83019370"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06142145,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9886999726295471,"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/T10727","display_name":"Ultrasound Imaging and Elastography","score":0.9853000044822693,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6899930238723755},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5900799632072449},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5504027605056763},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5386881828308105},{"id":"https://openalex.org/keywords/ultrasound-imaging","display_name":"Ultrasound imaging","score":0.5292448401451111},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4855337142944336},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34353893995285034},{"id":"https://openalex.org/keywords/ultrasound","display_name":"Ultrasound","score":0.3375977575778961},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.1373172402381897},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.08717381954193115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6899930238723755},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5900799632072449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5504027605056763},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5386881828308105},{"id":"https://openalex.org/C2986892559","wikidata":"https://www.wikidata.org/wiki/Q234904","display_name":"Ultrasound imaging","level":3,"score":0.5292448401451111},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4855337142944336},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34353893995285034},{"id":"https://openalex.org/C143753070","wikidata":"https://www.wikidata.org/wiki/Q162564","display_name":"Ultrasound","level":2,"score":0.3375977575778961},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.1373172402381897},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.08717381954193115}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10888253","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888253","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334678","display_name":"European Research Council","ror":"https://ror.org/0472cxd90"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2885749203","https://openalex.org/W2968947847","https://openalex.org/W3013692475","https://openalex.org/W3129022930","https://openalex.org/W4250955649","https://openalex.org/W4366140362","https://openalex.org/W4372342944","https://openalex.org/W4388118382","https://openalex.org/W4391594085","https://openalex.org/W4401879975","https://openalex.org/W4410112344","https://openalex.org/W6610566761","https://openalex.org/W6638116569","https://openalex.org/W6638667902","https://openalex.org/W6640963894","https://openalex.org/W6731370813","https://openalex.org/W6739901393","https://openalex.org/W6755977528","https://openalex.org/W6766978945","https://openalex.org/W6786494455","https://openalex.org/W6845513857","https://openalex.org/W6866443539"],"related_works":["https://openalex.org/W4250133764","https://openalex.org/W2391770021","https://openalex.org/W2613177006","https://openalex.org/W4390298813","https://openalex.org/W2990800024","https://openalex.org/W4247495643","https://openalex.org/W3032126157","https://openalex.org/W2182698094","https://openalex.org/W4240101417","https://openalex.org/W2370916954"],"abstract_inverted_index":{"Ultrasound":[0],"images":[1],"are":[2,160],"commonly":[3],"formed":[4],"by":[5,150],"sequential":[6],"acquisition":[7],"of":[8,14,23,109],"beam-steered":[9],"scan-lines.":[10],"Minimizing":[11],"the":[12,80,93,98,102,106,110,117,156],"number":[13],"required":[15],"scan-lines":[16],"can":[17],"significantly":[18],"enhance":[19],"frame":[20,108],"rate,":[21],"field":[22],"view,":[24],"energy":[25],"efficiency,":[26],"and":[27,83,105,123,135,155],"data":[28],"transfer":[29],"speeds.":[30],"Existing":[31],"approaches":[32],"typically":[33],"use":[34],"static":[35],"subsampling":[36,54,94],"schemes":[37],"in":[38,77,162],"combination":[39],"with":[40],"sparsity-based":[41],"or,":[42],"more":[43],"recently,":[44],"deep-learning-based":[45],"recovery.":[46],"In":[47],"this":[48],"work,":[49],"we":[50,91],"introduce":[51],"an":[52,70],"adaptive":[53],"method":[55,129],"that":[56,96,125],"maximizes":[57,97],"intrinsic":[58],"information":[59,100],"gain":[60],"in-situ,":[61],"employing":[62],"a":[63,84],"Sylvester":[64],"Normalizing":[65],"Flow":[66],"encoder":[67],"to":[68],"infer":[69],"approximate":[71],"Bayesian":[72,81],"posterior":[73,82,153],"under":[74],"partial":[75],"observation":[76],"real-time.":[78],"Using":[79],"deep":[85],"generative":[86],"model":[87],"for":[88,171],"future":[89],"observations,":[90,104],"determine":[92],"scheme":[95,158],"mutual":[99],"between":[101],"subsampled":[103],"next":[107],"video.":[111],"We":[112],"evaluate":[113],"our":[114,126],"approach":[115],"using":[116],"EchoNet":[118],"cardiac":[119],"ultrasound":[120,174],"video":[121],"dataset":[122],"demonstrate":[124],"active":[127],"sampling":[128,157],"outperforms":[130],"competitive":[131],"baselines,":[132],"including":[133],"uniform":[134],"variable-density":[136],"random":[137],"sampling,":[138],"as":[139,141],"well":[140],"equidistantly":[142],"spaced":[143],"scanlines,":[144],"improving":[145],"mean":[146],"absolute":[147],"reconstruction":[148],"error":[149],"15%.":[151],"Moreover,":[152],"inference":[154],"generation":[159],"performed":[161],"just":[163],"0.015":[164],"seconds":[165],"(66Hz),":[166],"making":[167],"it":[168],"fast":[169],"enough":[170],"real-time":[172],"2D":[173],"imaging":[175],"applications.":[176]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}