{"id":"https://openalex.org/W2913372409","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633086","title":"Generative Adversarial Networks with Dense Connection for Optical Coherence Tomography Images Denoising","display_name":"Generative Adversarial Networks with Dense Connection for Optical Coherence Tomography Images Denoising","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2913372409","doi":"https://doi.org/10.1109/cisp-bmei.2018.8633086","mag":"2913372409"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2018.8633086","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633086","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5110596620","display_name":"Aihui Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Aihui Yu","raw_affiliation_strings":["College of Computer Science and Technology, Wuhan University of Science and technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Wuhan University of Science and technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100409053","display_name":"Xiaoming Liu","orcid":"https://orcid.org/0000-0003-3467-5607"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoming Liu","raw_affiliation_strings":["College of Computer Science and Technology, Wuhan University of Science and technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Wuhan University of Science and technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089675652","display_name":"Xiangkai Wei","orcid":"https://orcid.org/0009-0000-4313-0014"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangkai Wei","raw_affiliation_strings":["College of Computer Science and Technology, Wuhan University of Science and technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Wuhan University of Science and technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101765986","display_name":"Tianyu Fu","orcid":"https://orcid.org/0000-0002-0903-6697"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyu Fu","raw_affiliation_strings":["College of Computer Science and Technology, Wuhan University of Science and technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Wuhan University of Science and technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100407381","display_name":"Dong Liu","orcid":"https://orcid.org/0000-0001-9100-2906"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Liu","raw_affiliation_strings":["College of Computer Science and Technology, Wuhan University of Science and technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Wuhan University of Science and technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5110596620"],"corresponding_institution_ids":["https://openalex.org/I43922553"],"apc_list":null,"apc_paid":null,"fwci":0.3134,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.64135954,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.998199999332428,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.998199999332428,"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/T11569","display_name":"Optical Coherence Tomography Applications","score":0.9980999827384949,"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"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9958999752998352,"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/optical-coherence-tomography","display_name":"Optical coherence tomography","score":0.8799646496772766},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7911931276321411},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7543925046920776},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6962326765060425},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.6237853765487671},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5985140800476074},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5526384711265564},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5368130207061768},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.5217103362083435},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.515545129776001},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.503560483455658},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.4386560320854187},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4342305064201355},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.43173158168792725},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4103030264377594},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.4087703824043274},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3496472239494324},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.08614557981491089},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07816764712333679}],"concepts":[{"id":"https://openalex.org/C2778818243","wikidata":"https://www.wikidata.org/wiki/Q899552","display_name":"Optical coherence tomography","level":2,"score":0.8799646496772766},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7911931276321411},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7543925046920776},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6962326765060425},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.6237853765487671},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5985140800476074},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5526384711265564},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5368130207061768},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.5217103362083435},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.515545129776001},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.503560483455658},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.4386560320854187},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4342305064201355},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.43173158168792725},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4103030264377594},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.4087703824043274},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3496472239494324},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.08614557981491089},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07816764712333679},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2018.8633086","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2018.8633086","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1485262465","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1885185971","https://openalex.org/W1924619199","https://openalex.org/W2021229920","https://openalex.org/W2023154442","https://openalex.org/W2026516529","https://openalex.org/W2056370875","https://openalex.org/W2085692415","https://openalex.org/W2099471712","https://openalex.org/W2103015025","https://openalex.org/W2108207814","https://openalex.org/W2123222766","https://openalex.org/W2132680427","https://openalex.org/W2173905264","https://openalex.org/W2331128040","https://openalex.org/W2476548250","https://openalex.org/W2508457857","https://openalex.org/W2511730936","https://openalex.org/W2523714292","https://openalex.org/W2586047034","https://openalex.org/W2617128058","https://openalex.org/W2738053461","https://openalex.org/W2883235649","https://openalex.org/W2890692913","https://openalex.org/W2949117887","https://openalex.org/W2963446712","https://openalex.org/W2963470893","https://openalex.org/W2963920537","https://openalex.org/W3104725225","https://openalex.org/W4293439130","https://openalex.org/W6637373629","https://openalex.org/W6640174519","https://openalex.org/W6685639397","https://openalex.org/W6741681911"],"related_works":["https://openalex.org/W2065648684","https://openalex.org/W2009383287","https://openalex.org/W2042914788","https://openalex.org/W2182190754","https://openalex.org/W4321264664","https://openalex.org/W2055824452","https://openalex.org/W2121688719","https://openalex.org/W2727313114","https://openalex.org/W2016481886","https://openalex.org/W4241911733"],"abstract_inverted_index":{"Optical":[0],"coherence":[1],"tomography":[2],"(OCT)":[3],"is":[4,15,82,100],"widely":[5],"used":[6],"in":[7,43],"the":[8,27,33,44,94,104,108,114],"diagnosis":[9],"of":[10,107,117],"ophthalmic":[11],"diseases.":[12],"However,":[13],"OCT":[14,66,70,87,91,121],"affected":[16],"by":[17],"ubiquitous":[18],"speckle":[19],"noise":[20,34],"which":[21],"make":[22],"it":[23],"difficult":[24],"to":[25,48,63,84,102],"analysis":[26],"retinal":[28],"structures.":[29],"To":[30],"efficiently":[31],"remove":[32],"as":[35,37],"well":[36],"preserve":[38],"clinical":[39],"detail":[40],"information":[41],"contained":[42],"images,":[45],"we":[46],"suggest":[47],"train":[49],"a":[50,58],"denoise":[51],"generative":[52],"adversarial":[53,98],"network":[54,62,76,119],"(DNGAN)":[55],"jointly":[56],"with":[57,78],"densely":[59],"connected":[60],"convolutional":[61,74],"estimate":[64],"clean":[65,90],"images":[67],"from":[68],"noisy":[69,86],"images.":[71,122],"A":[72],"generator":[73],"neural":[75],"(CNN)":[77],"several":[79],"dense":[80],"connections,":[81],"trained":[83,101],"transform":[85],"image":[88],"into":[89],"image.":[92],"At":[93],"same":[95],"time,":[96],"an":[97],"CNN":[99],"improve":[103],"denoising":[105],"performance":[106,116],"generator.":[109],"The":[110],"experimental":[111],"results":[112],"demonstrate":[113],"superior":[115],"our":[118],"on":[120]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
