{"id":"https://openalex.org/W3204914111","doi":"https://doi.org/10.1145/3472634.3474074","title":"Deformation Medical Image Registration Algorithm Based On Deep Prior Optical Flow Network","display_name":"Deformation Medical Image Registration Algorithm Based On Deep Prior Optical Flow Network","publication_year":2021,"publication_date":"2021-07-30","ids":{"openalex":"https://openalex.org/W3204914111","doi":"https://doi.org/10.1145/3472634.3474074","mag":"3204914111"},"language":"en","primary_location":{"id":"doi:10.1145/3472634.3474074","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3472634.3474074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Turing Award Celebration Conference - China ( ACM TURC 2021)","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/A5082958570","display_name":"Lujin Li","orcid":null},"institutions":[{"id":"https://openalex.org/I24201400","display_name":"Chengdu University of Information Technology","ror":"https://ror.org/01yxwrh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I24201400"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lujin Li","raw_affiliation_strings":["Chengdu University of Information Technology, China"],"affiliations":[{"raw_affiliation_string":"Chengdu University of Information Technology, China","institution_ids":["https://openalex.org/I24201400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101760131","display_name":"Hailiang Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I24201400","display_name":"Chengdu University of Information Technology","ror":"https://ror.org/01yxwrh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I24201400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hailiang Wang","raw_affiliation_strings":["Chengdu University of Information Technology, China"],"affiliations":[{"raw_affiliation_string":"Chengdu University of Information Technology, China","institution_ids":["https://openalex.org/I24201400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028521210","display_name":"Jinrong Hu","orcid":"https://orcid.org/0000-0001-7732-8141"},"institutions":[{"id":"https://openalex.org/I24201400","display_name":"Chengdu University of Information Technology","ror":"https://ror.org/01yxwrh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I24201400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinrong Hu","raw_affiliation_strings":["Chengdu University of Information Technology, China"],"affiliations":[{"raw_affiliation_string":"Chengdu University of Information Technology, China","institution_ids":["https://openalex.org/I24201400"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030335492","display_name":"Yan Zhang","orcid":"https://orcid.org/0000-0001-5738-9537"},"institutions":[{"id":"https://openalex.org/I141301092","display_name":"China Meteorological Administration","ror":"https://ror.org/00bx3rb98","country_code":"CN","type":"government","lineage":["https://openalex.org/I141301092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Zhang","raw_affiliation_strings":["China Meteorological Administration (CMA), China"],"affiliations":[{"raw_affiliation_string":"China Meteorological Administration (CMA), China","institution_ids":["https://openalex.org/I141301092"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5082958570"],"corresponding_institution_ids":["https://openalex.org/I24201400"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12767974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"210","last_page":"215"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9980000257492065,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9980000257492065,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9973000288009644,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9929999709129333,"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/computer-science","display_name":"Computer science","score":0.7633757591247559},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7270095348358154},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.6569168567657471},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.6534850597381592},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5832641124725342},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4987947940826416},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48882052302360535},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.4797281324863434},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4686160683631897},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46608346700668335},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.4266374409198761},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3318706452846527},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32623326778411865},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1003202497959137}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7633757591247559},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7270095348358154},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.6569168567657471},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.6534850597381592},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5832641124725342},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4987947940826416},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48882052302360535},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.4797281324863434},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4686160683631897},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46608346700668335},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.4266374409198761},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3318706452846527},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32623326778411865},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1003202497959137},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"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/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3472634.3474074","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3472634.3474074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Turing Award Celebration Conference - China ( ACM TURC 2021)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1230023165","https://openalex.org/W1865513531","https://openalex.org/W1985586071","https://openalex.org/W2044011870","https://openalex.org/W2090518410","https://openalex.org/W2126393454","https://openalex.org/W2152697758","https://openalex.org/W2158167845","https://openalex.org/W2765903437"],"related_works":["https://openalex.org/W4293320219","https://openalex.org/W2953246223","https://openalex.org/W3110074278","https://openalex.org/W4283584549","https://openalex.org/W2554314924","https://openalex.org/W4288256692","https://openalex.org/W2998859928","https://openalex.org/W3156863413","https://openalex.org/W4381885966","https://openalex.org/W2969399009"],"abstract_inverted_index":{"Deep":[0,38],"convolutional":[1,105,146],"networks":[2],"have":[3],"become":[4],"a":[5,29,50,71,85,110],"common":[6,145],"tool":[7],"for":[8,138],"image":[9,33,55,90,115,121,131,135,184,191,252],"generation":[10],"and":[11,77,132,143,166,204,242,257],"reconstruction.":[12],"Unlike":[13],"people":[14],"who":[15],"attribute":[16],"their":[17],"excellent":[18],"performance":[19],"to":[20,94,108,123,136,199,213,220,224],"the":[21,35,44,81,98,103,125,129,133,139,144,155,170,189,201,205,208,217,225,239],"prior":[22],"information":[23,57,65,117,151,165,198],"that":[24,43,63,80,232],"they":[25],"can":[26,48,102,236],"learn":[27],"from":[28],"large":[30,51,72,111],"number":[31,52,73,112],"of":[32,37,53,74,88,100,113,150,207],"samples,":[34],"author":[36],"Image":[39],"Prior":[40],"(DIP)":[41],"believes":[42],"generator":[45,194],"The":[46,193],"network":[47,83,147,195,210],"capture":[49,87,109,124,152],"low-level":[54,114],"statistical":[56,116],"before":[58],"any":[59],"learning,":[60],"which":[61],"means":[62],"this":[64],"may":[66],"not":[67,174],"be":[68,118],"learned":[69],"through":[70],"data":[75],"sets,":[76],"it":[78,222],"verifies":[79],"CNN":[82],"has":[84],"better":[86,247],"natural":[89],"distribution":[91],"information.":[92],"Ability":[93],"imitate.":[95],"Inspired":[96],"by":[97],"idea":[99],"DIP,":[101],"deep":[104],"network's":[106],"ability":[107],"used":[119,212],"in":[120],"registration":[122,159,171,185,240,244,254],"deformation":[126,168,202,218,227],"field":[127,219],"between":[128],"floating":[130],"target":[134],"compensate":[137],"traditional":[140,156],"manual":[141],"features":[142,148],"Limitations":[149],"capabilities.":[153],"Because":[154],"optical":[157,181],"flow":[158,182],"method":[160,186],"only":[161],"relies":[162],"on":[163,188],"gray":[164],"gradient-driven":[167],"registration,":[169],"result":[172],"is":[173,211,246],"accurate":[175],"enough.":[176],"Therefore,":[177],"we":[178],"propose":[179],"an":[180],"medical":[183,251],"based":[187],"depth":[190],"prior.":[192],"extracts":[196],"feature":[197],"generate":[200],"field,":[203],"discriminator":[206],"GAN":[209],"further":[214],"accurately":[215],"improve":[216,238],"make":[221],"closer":[223],"real":[226],"field.":[228],"Experimental":[229],"results":[230],"show":[231],"our":[233],"proposed":[234],"algorithm":[235],"effectively":[237],"accuracy,":[241],"its":[243],"accuracy":[245],"than":[248],"Demons":[249],"algorithm,":[250],"professional":[253],"software":[255],"Elastix":[256],"Scale":[258],"Invariant":[259],"Feature":[260],"Transform":[261],"(SIFT)":[262],"Flow":[263],"algorithm.":[264]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
