{"id":"https://openalex.org/W4385545459","doi":"https://doi.org/10.58530/2022/3655","title":"SNR boost in whole-body DWIBS utilizing deep learning constrained Compressed SENSE reconstruction","display_name":"SNR boost in whole-body DWIBS utilizing deep learning constrained Compressed SENSE reconstruction","publication_year":2023,"publication_date":"2023-08-03","ids":{"openalex":"https://openalex.org/W4385545459","doi":"https://doi.org/10.58530/2022/3655"},"language":"en","primary_location":{"id":"doi:10.58530/2022/3655","doi":"https://doi.org/10.58530/2022/3655","is_oa":false,"landing_page_url":"http://dx.doi.org/10.58530/2022/3655","pdf_url":null,"source":{"id":"https://openalex.org/S4393917449","display_name":"Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition","issn_l":"1524-6965","issn":["1524-6965","1545-4428"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISMRM Annual Meeting","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5036205540","display_name":"Masami Yoneyama","orcid":"https://orcid.org/0000-0003-3517-2120","observed_orcids":["https://orcid.org/0000-0003-3517-2120"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Masami Yoneyama","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076344498","display_name":"Takashige Yoshida","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takashige Yoshida","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048919592","display_name":"Johannes Peeters","orcid":"https://orcid.org/0000-0001-6639-0863","observed_orcids":["https://orcid.org/0000-0001-6639-0863"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Johannes Peeters","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089111452","display_name":"Jihun Kwon","orcid":"https://orcid.org/0000-0003-1810-0205","observed_orcids":["https://orcid.org/0000-0003-1810-0205"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jihun Kwon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015993618","display_name":"Yasutomo Katsumata","orcid":"https://orcid.org/0009-0008-3196-8248","observed_orcids":["https://orcid.org/0009-0008-3196-8248"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yasutomo Katsumata","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100450343","display_name":"Shuo Zhang","orcid":"https://orcid.org/0000-0001-7376-283X","observed_orcids":["https://orcid.org/0000-0001-7376-283X","https://orcid.org/0000-0001-6006-0978"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuo Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5014180471","display_name":"Marc VAN CAUTEREN","orcid":"https://orcid.org/0000-0002-9654-1746","observed_orcids":["https://orcid.org/0000-0002-9654-1746"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marc Van Cauteren","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.572,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62930412,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9854000210762024,"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"}},"topics":[{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9854000210762024,"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/T11885","display_name":"MRI in cancer diagnosis","score":0.008799999952316284,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.002199999988079071,"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/dwibs","display_name":"DWIBS","score":0.8330000042915344},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"compressed sensing","score":0.6940000057220459},{"id":"https://openalex.org/keywords/senses","display_name":"senses","score":0.5889999866485596},{"id":"https://openalex.org/keywords/deep-learning-reconstruction","display_name":"deep learning reconstruction","score":0.671999990940094},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"signal-to-noise ratio","score":0.8870000243186951},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"noise reduction","score":0.503000020980835},{"id":"https://openalex.org/keywords/lesion-conspicuity","display_name":"lesion conspicuity","score":0.9259999990463257},{"id":"https://openalex.org/keywords/whole-body-mri","display_name":"whole-body MRI","score":0.5709999799728394}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7269445657730103},{"id":"https://openalex.org/C13483470","wikidata":"https://www.wikidata.org/wiki/Q1470152","display_name":"Coronal plane","level":2,"score":0.6904593706130981},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5728242993354797},{"id":"https://openalex.org/C2776410896","wikidata":"https://www.wikidata.org/wiki/Q7997551","display_name":"Whole body imaging","level":3,"score":0.570151150226593},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.4950024485588074},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4714544713497162},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.4483034014701843},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4456002116203308},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.13938987255096436},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13771024346351624},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.13656136393547058},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.0994216799736023},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08155772089958191},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.06787377595901489},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.58530/2022/3655","doi":"https://doi.org/10.58530/2022/3655","is_oa":false,"landing_page_url":"http://dx.doi.org/10.58530/2022/3655","pdf_url":null,"source":{"id":"https://openalex.org/S4393917449","display_name":"Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition","issn_l":"1524-6965","issn":["1524-6965","1545-4428"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISMRM Annual Meeting","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6240000128746033,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4404745786","https://openalex.org/W4385545591","https://openalex.org/W4385555372","https://openalex.org/W4385543145","https://openalex.org/W4385545779","https://openalex.org/W4394824066","https://openalex.org/W2387668276","https://openalex.org/W4401576229","https://openalex.org/W4385545649","https://openalex.org/W2796173250"],"abstract_inverted_index":{"Diffusion":[0],"weighted":[1],"whole":[2,16],"body":[3,7,17],"imaging":[4,18],"with":[5],"background":[6],"signal":[8],"suppression":[9],"(DWIBS)":[10],"is":[11],"an":[12],"important":[13],"tool":[14],"for":[15],"to":[19,29,46,51],"e.g.":[20],"visualize":[21],"malignant":[22],"tumor":[23],"and":[24,61,83],"abnormal":[25],"lymph":[26],"nodes.":[27],"Next":[28],"the":[30,47,75,79],"low":[31],"intrinsic":[32],"SNR":[33,43],"of":[34],"DWIBS,":[35],"direct":[36,65],"coronal":[37,66],"DWIBS":[38,67],"can":[39],"suffer":[40],"from":[41],"another":[42],"penalty":[44],"due":[45],"high":[48],"acceleration":[49],"factors":[50],"minimize":[52],"distortion.":[53],"In":[54],"this":[55],"work,":[56],"we":[57],"compare":[58],"SENSE,":[59],"C-SENSE":[60],"C-SENSE-AI":[62],"(CS-AI)":[63],"accelerated":[64],"scans.":[68],"Results":[69],"indicate":[70],"that":[71],"CS-AI":[72],"clearly":[73],"reduces":[74],"noise":[76],"artifacts,":[77],"boosts":[78],"overall":[80],"image":[81],"SNR,":[82],"improves":[84],"lesion":[85],"conspicuity.":[86]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2023-08-04T00:00:00"}
