{"id":"https://openalex.org/W4362489302","doi":"https://doi.org/10.1117/12.2654298","title":"High-quality label-free prediction of fluorescence images through stimulated Raman scattering imaging and recurrent deep neural network","display_name":"High-quality label-free prediction of fluorescence images through stimulated Raman scattering imaging and recurrent deep neural network","publication_year":2023,"publication_date":"2023-04-03","ids":{"openalex":"https://openalex.org/W4362489302","doi":"https://doi.org/10.1117/12.2654298"},"language":"en","primary_location":{"id":"doi:10.1117/12.2654298","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1117/12.2654298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment","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/A5054714748","display_name":"Tianrun Chen","orcid":"https://orcid.org/0000-0003-0177-0157"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianrun Chen","raw_affiliation_strings":["Zhejiang Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Zhejiang Univ. (China)","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057492564","display_name":"Ying Zang","orcid":"https://orcid.org/0000-0002-1361-1500"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Zang","raw_affiliation_strings":["Huzhou Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Huzhou Univ. (China)","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100360684","display_name":"Jia Zhang","orcid":"https://orcid.org/0000-0002-1433-6651"},"institutions":[{"id":"https://openalex.org/I4210118178","display_name":"Yangzhou Polytechnic Institute","ror":"https://ror.org/02grzhe48","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210118178"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Zhang","raw_affiliation_strings":["Yangzhou Polytechnic College (China)"],"affiliations":[{"raw_affiliation_string":"Yangzhou Polytechnic College (China)","institution_ids":["https://openalex.org/I4210118178"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084657803","display_name":"Delong Zhang","orcid":"https://orcid.org/0000-0002-9734-3573"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Delong Zhang","raw_affiliation_strings":["Zhejiang Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Zhejiang Univ. (China)","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054714748"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.3667,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7538335,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"108","issue":null,"first_page":"42","last_page":"42"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9901000261306763,"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/computer-science","display_name":"Computer science","score":0.7678794264793396},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7297961115837097},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.6968058347702026},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6578390002250671},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5994752645492554},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.5601426959037781},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44339919090270996},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.4275899827480316},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.42661014199256897},{"id":"https://openalex.org/keywords/raman-scattering","display_name":"Raman scattering","score":0.41911548376083374},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23830464482307434},{"id":"https://openalex.org/keywords/raman-spectroscopy","display_name":"Raman spectroscopy","score":0.13648009300231934}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7678794264793396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7297961115837097},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.6968058347702026},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6578390002250671},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5994752645492554},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.5601426959037781},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44339919090270996},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.4275899827480316},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.42661014199256897},{"id":"https://openalex.org/C169573571","wikidata":"https://www.wikidata.org/wiki/Q466824","display_name":"Raman scattering","level":3,"score":0.41911548376083374},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23830464482307434},{"id":"https://openalex.org/C40003534","wikidata":"https://www.wikidata.org/wiki/Q862228","display_name":"Raman spectroscopy","level":2,"score":0.13648009300231934},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2654298","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1117/12.2654298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment","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":25,"referenced_works":["https://openalex.org/W2043822655","https://openalex.org/W2054249414","https://openalex.org/W2072723742","https://openalex.org/W2115318086","https://openalex.org/W2157331557","https://openalex.org/W2161704908","https://openalex.org/W2332583381","https://openalex.org/W2614949728","https://openalex.org/W2797749376","https://openalex.org/W2910683834","https://openalex.org/W2949493305","https://openalex.org/W2986934761","https://openalex.org/W3098491829","https://openalex.org/W3100420029","https://openalex.org/W3134761005","https://openalex.org/W4210723357","https://openalex.org/W4236544657","https://openalex.org/W4236689535","https://openalex.org/W4242623031","https://openalex.org/W4248415096","https://openalex.org/W4320013936","https://openalex.org/W4394321870","https://openalex.org/W6639824700","https://openalex.org/W6683258052","https://openalex.org/W6774733904"],"related_works":["https://openalex.org/W2385859805","https://openalex.org/W2530972254","https://openalex.org/W2374013449","https://openalex.org/W73545470","https://openalex.org/W2364381299","https://openalex.org/W2374430585","https://openalex.org/W2377397762","https://openalex.org/W2361654993","https://openalex.org/W2392886218","https://openalex.org/W2530686067"],"abstract_inverted_index":{"Multiple":[0],"imaging":[1,22,27],"modalities":[2],"are":[3],"commonly":[4],"jointly":[5],"used":[6],"for":[7,48],"investigating":[8],"biological":[9,147],"phenomena":[10],"or":[11],"diagnosis":[12],"purposes.":[13],"In":[14],"this":[15,49],"study,":[16],"we":[17,59],"propose":[18],"a":[19,123],"deep-learning-based":[20],"cross-modality":[21,133],"technique":[23],"that":[24,79,126],"utilizes":[25],"one":[26],"modality":[28],"to":[29,103],"computationally":[30],"predict":[31],"another.":[32],"A":[33],"novel":[34],"neural":[35,98],"network":[36,99],"architecture,":[37],"featuring":[38],"recurrent":[39],"multi-stage":[40,116],"refinement":[41,117],"controlled":[42],"by":[43],"gated":[44],"activation,":[45],"was":[46,101],"developed":[47],"purpose.":[50],"To":[51],"demonstrate":[52],"the":[53,56,76,83,115,128,142],"effectiveness":[54],"of":[55,75,92,130,144],"proposed":[57,120],"method,":[58],"conducted":[60],"experiments":[61,77],"on":[62],"predicting":[63],"organelle":[64],"fluorescence":[65],"images":[66],"from":[67],"stimulated":[68],"Raman":[69],"scattering":[70],"(SRS)":[71],"imaging.":[72,148],"The":[73,97,119],"results":[74],"indicate":[78],"our":[80],"method":[81,121],"outperforms":[82],"current":[84,131],"state-of-the-art":[85],"techniques":[86,136],"across":[87],"multiple":[88],"datasets,":[89],"in":[90,141],"terms":[91],"both":[93],"accuracy":[94,113],"and":[95,110,137,146],"efficiency.":[96],"architecture":[100],"able":[102],"produce":[104],"high-quality":[105],"predictions":[106],"with":[107],"clear":[108],"boundaries":[109],"high":[111],"prediction":[112,135],"through":[114],"process.":[118],"presents":[122],"versatile":[124],"framework":[125],"addresses":[127],"limitations":[129],"deep-learning-enabled":[132],"image":[134],"has":[138],"potential":[139],"applications":[140],"field":[143],"medical":[145]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
