{"id":"https://openalex.org/W2806077003","doi":"https://doi.org/10.1109/isbi.2018.8363861","title":"Placental maturity grading via hybrid descriptors based on fisher vector","display_name":"Placental maturity grading via hybrid descriptors based on fisher vector","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2806077003","doi":"https://doi.org/10.1109/isbi.2018.8363861","mag":"2806077003"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2018.8363861","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363861","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","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/A5054864573","display_name":"Feng Jiang","orcid":"https://orcid.org/0000-0001-8342-1211"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Feng Jiang","raw_affiliation_strings":["School of Biomedical Engineering, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065374358","display_name":"Dong Ni","orcid":"https://orcid.org/0000-0002-9146-6003"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong Ni","raw_affiliation_strings":["School of Biomedical Engineering, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053298653","display_name":"Siping Chen","orcid":"https://orcid.org/0000-0001-7953-8126"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siping Chen","raw_affiliation_strings":["School of Biomedical Engineering, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100337338","display_name":"Yuan Yao","orcid":"https://orcid.org/0000-0002-2705-6245"},"institutions":[{"id":"https://openalex.org/I4210128628","display_name":"Peking University Shenzhen Hospital","ror":"https://ror.org/03kkjyb15","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128628"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Yao","raw_affiliation_strings":["Department of Ultrasound, Hospital of Nan fang Medical University, Shenzhen, P. R. China"],"affiliations":[{"raw_affiliation_string":"Department of Ultrasound, Hospital of Nan fang Medical University, Shenzhen, P. R. China","institution_ids":["https://openalex.org/I4210128628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042658727","display_name":"Minh Hung Le","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Minh Hung Le","raw_affiliation_strings":["School of Biomedical Engineering, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046543349","display_name":"Tianfu Wang","orcid":"https://orcid.org/0000-0002-1248-1214"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tianfu Wang","raw_affiliation_strings":["School of Biomedical Engineering, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001212991","display_name":"Baiying Lei","orcid":"https://orcid.org/0000-0002-3087-2550"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baiying Lei","raw_affiliation_strings":["School of Biomedical Engineering, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5054864573"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06308942,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"24","issue":null,"first_page":"1517","last_page":"1520"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11374","display_name":"Cleft Lip and Palate Research","score":0.9769999980926514,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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/T11374","display_name":"Cleft Lip and Palate Research","score":0.9769999980926514,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9513999819755554,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11184","display_name":"Neonatal and fetal brain pathology","score":0.9107999801635742,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/support-vector-machine","display_name":"Support vector machine","score":0.7794767618179321},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7633593678474426},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7401496171951294},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6866818070411682},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6116769313812256},{"id":"https://openalex.org/keywords/grading","display_name":"Grading (engineering)","score":0.5592206716537476},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.545717716217041},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5308053493499756},{"id":"https://openalex.org/keywords/maturity","display_name":"Maturity (psychological)","score":0.44430550932884216},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35604095458984375},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0869896411895752}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7794767618179321},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7633593678474426},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7401496171951294},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6866818070411682},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6116769313812256},{"id":"https://openalex.org/C2777286243","wikidata":"https://www.wikidata.org/wiki/Q5591926","display_name":"Grading (engineering)","level":2,"score":0.5592206716537476},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.545717716217041},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5308053493499756},{"id":"https://openalex.org/C101433766","wikidata":"https://www.wikidata.org/wiki/Q3543263","display_name":"Maturity (psychological)","level":2,"score":0.44430550932884216},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35604095458984375},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0869896411895752},{"id":"https://openalex.org/C138496976","wikidata":"https://www.wikidata.org/wiki/Q175002","display_name":"Developmental psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2018.8363861","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363861","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1455359501","https://openalex.org/W1582640985","https://openalex.org/W1686810756","https://openalex.org/W1871835765","https://openalex.org/W1966385142","https://openalex.org/W1974716010","https://openalex.org/W1984309565","https://openalex.org/W2014584125","https://openalex.org/W2061715187","https://openalex.org/W2118425210","https://openalex.org/W2161381512","https://openalex.org/W2162915993","https://openalex.org/W2334043093","https://openalex.org/W2525445703","https://openalex.org/W2541749490","https://openalex.org/W4294375521","https://openalex.org/W4299518610","https://openalex.org/W6628461835","https://openalex.org/W6682132143","https://openalex.org/W6682778277","https://openalex.org/W6702711800"],"related_works":["https://openalex.org/W2064165679","https://openalex.org/W1588461101","https://openalex.org/W3208525924","https://openalex.org/W2591833644","https://openalex.org/W2885058781","https://openalex.org/W2791617766","https://openalex.org/W4293226380","https://openalex.org/W2090763504","https://openalex.org/W2010501276","https://openalex.org/W3127248583"],"abstract_inverted_index":{"Placental":[0],"maturity":[1,61],"grading":[2,131],"(PMG)":[3],"is":[4,27,125],"quite":[5],"essential":[6],"to":[7,50,58,93,97,114,128,158],"assess":[8],"fetal":[9],"growth":[10],"and":[11,29,71,88],"maternal":[12],"health.":[13],"To":[14],"this":[15],"date,":[16],"PMG":[17],"has":[18,170],"mostly":[19],"relied":[20],"on":[21,36,67,134],"the":[22,99,102,121,130,135,156],"clinician's":[23],"subjective":[24],"judgment,":[25],"which":[26],"time-consuming":[28],"subjective.":[30],"Traditional":[31],"machine":[32,153],"learning-based":[33],"methods":[34],"capitalize":[35],"handcrafted":[37],"features,":[38],"but":[39],"such":[40],"features":[41,90],"may":[42],"be":[43],"essentially":[44],"insufficient":[45],"for":[46],"PMG.":[47],"In":[48],"order":[49],"tackle":[51],"it,":[52],"we":[53,149],"propose":[54],"an":[55],"automatic":[56],"method":[57,169],"stage":[59],"placental":[60,160],"via":[62],"deep":[63,83,136],"hybrid":[64,95,116],"descriptors":[65,79,96,117,141],"based":[66,133],"B-mode":[68],"ultrasound":[69],"(BUS)":[70],"color":[72],"Doppler":[73],"energy":[74],"(CDE)":[75],"images.":[76,119],"Specifically,":[77],"convolutional":[78,84],"extracted":[80,140],"from":[81,118],"a":[82],"neural":[85],"network":[86],"(CNN)":[87],"handcraft":[89],"are":[91,112,142],"combined":[92,113],"form":[94],"boost":[98],"performance":[100,132],"of":[101],"proposed":[103,168],"method.":[104],"First,":[105],"different":[106],"models":[107],"with":[108],"various":[109],"feature":[110],"layers":[111],"obtain":[115],"Meanwhile,":[120],"transfer":[122],"learning":[123],"strategy":[124],"also":[126],"utilized":[127],"enhance":[129],"representation":[137],"features.":[138],"Then,":[139],"encoded":[143],"by":[144],"Fisher":[145],"vector":[146,152],"(FV).":[147],"Finally,":[148],"use":[150],"support":[151],"(SVM)":[154],"as":[155],"classifier":[157],"grade":[159],"maturity.":[161],"The":[162],"experimental":[163],"results":[164],"demonstrate":[165],"that":[166],"our":[167],"achieved":[171],"remarkable":[172],"staging":[173],"performance.":[174]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}