{"id":"https://openalex.org/W2997925807","doi":"https://doi.org/10.1109/access.2019.2961268","title":"An Optimized Registration Method Based on Distribution Similarity and DVF Smoothness for 3D PET and CT Images","display_name":"An Optimized Registration Method Based on Distribution Similarity and DVF Smoothness for 3D PET and CT Images","publication_year":2019,"publication_date":"2019-12-24","ids":{"openalex":"https://openalex.org/W2997925807","doi":"https://doi.org/10.1109/access.2019.2961268","mag":"2997925807"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2961268","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2961268","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08937543.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08937543.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032940701","display_name":"Hongjian Kang","orcid":"https://orcid.org/0000-0002-6627-1482"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongjian Kang","raw_affiliation_strings":["Software College, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-6627-1482","affiliations":[{"raw_affiliation_string":"Software College, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073727134","display_name":"Huiyan Jiang","orcid":"https://orcid.org/0000-0002-1428-8776"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiyan Jiang","raw_affiliation_strings":["Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China","Software College, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-1428-8776","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"Software College, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035435894","display_name":"Xiangrong Zhou","orcid":"https://orcid.org/0000-0001-8737-4977"},"institutions":[{"id":"https://openalex.org/I42405503","display_name":"Gifu University","ror":"https://ror.org/024exxj48","country_code":"JP","type":"education","lineage":["https://openalex.org/I42405503"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiangrong Zhou","raw_affiliation_strings":["Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu-shi, Japan"],"raw_orcid":"https://orcid.org/0000-0001-8737-4977","affiliations":[{"raw_affiliation_string":"Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu-shi, Japan","institution_ids":["https://openalex.org/I42405503"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001236860","display_name":"Hengjian Yu","orcid":"https://orcid.org/0000-0003-3053-3652"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengjian Yu","raw_affiliation_strings":["Software College, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0003-3053-3652","affiliations":[{"raw_affiliation_string":"Software College, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090297441","display_name":"Takeshi Hara","orcid":"https://orcid.org/0000-0002-0235-238X"},"institutions":[{"id":"https://openalex.org/I42405503","display_name":"Gifu University","ror":"https://ror.org/024exxj48","country_code":"JP","type":"education","lineage":["https://openalex.org/I42405503"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takeshi Hara","raw_affiliation_strings":["Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu-shi, Japan"],"raw_orcid":"https://orcid.org/0000-0002-0235-238X","affiliations":[{"raw_affiliation_string":"Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu-shi, Japan","institution_ids":["https://openalex.org/I42405503"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027406783","display_name":"Hiroshi Fujita","orcid":"https://orcid.org/0000-0002-2936-9296"},"institutions":[{"id":"https://openalex.org/I42405503","display_name":"Gifu University","ror":"https://ror.org/024exxj48","country_code":"JP","type":"education","lineage":["https://openalex.org/I42405503"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Fujita","raw_affiliation_strings":["Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu-shi, Japan"],"raw_orcid":"https://orcid.org/0000-0002-2936-9296","affiliations":[{"raw_affiliation_string":"Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering, Gifu University, Gifu-shi, Japan","institution_ids":["https://openalex.org/I42405503"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021827481","display_name":"Yudong Yao","orcid":"https://orcid.org/0000-0003-3868-0593"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu-Dong Yao","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, USA"],"raw_orcid":"https://orcid.org/0000-0003-3868-0593","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, USA","institution_ids":["https://openalex.org/I108468826"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.5955,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.73028904,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"8","issue":null,"first_page":"1135","last_page":"1145"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994999766349792,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994999766349792,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9991999864578247,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9986000061035156,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.7826592326164246},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7804869413375854},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.6068828105926514},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5910438299179077},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5540489554405212},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4746991991996765},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4438555836677551},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4368632137775421},{"id":"https://openalex.org/keywords/standard-test-image","display_name":"Standard test image","score":0.43284448981285095},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.4198625683784485},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.4108165502548218},{"id":"https://openalex.org/keywords/nuclear-medicine","display_name":"Nuclear medicine","score":0.37529677152633667},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33033448457717896},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.24179697036743164},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24164032936096191},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.16454344987869263}],"concepts":[{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.7826592326164246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7804869413375854},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.6068828105926514},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5910438299179077},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5540489554405212},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4746991991996765},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4438555836677551},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4368632137775421},{"id":"https://openalex.org/C180462255","wikidata":"https://www.wikidata.org/wiki/Q3559736","display_name":"Standard test image","level":4,"score":0.43284448981285095},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.4198625683784485},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.4108165502548218},{"id":"https://openalex.org/C2989005","wikidata":"https://www.wikidata.org/wiki/Q214963","display_name":"Nuclear medicine","level":1,"score":0.37529677152633667},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33033448457717896},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.24179697036743164},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24164032936096191},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.16454344987869263}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2961268","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2961268","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08937543.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:80e2d13819b7447fa8d39f1d1290994f","is_oa":true,"landing_page_url":"https://doaj.org/article/80e2d13819b7447fa8d39f1d1290994f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 1135-1145 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2961268","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2961268","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08937543.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2689429656","display_name":"\u57fa\u4e8ePET/CT\u5f71\u50cf\u7ec4\u5b66\u7684\u5168\u8eab\u6dcb\u5df4\u7624\u667a\u80fd\u8bca\u65ad\u5173\u952e\u6280\u672f\u7684\u7814\u7a76","funder_award_id":"61872075","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3134019175","display_name":null,"funder_award_id":"26108005","funder_id":"https://openalex.org/F4320320912","funder_display_name":"Ministry of Education, Culture, Sports, Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320320912","display_name":"Ministry of Education, Culture, Sports, Science and Technology","ror":"https://ror.org/048rj2z13"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W321648571","https://openalex.org/W603908379","https://openalex.org/W1522301498","https://openalex.org/W1874027545","https://openalex.org/W2033794939","https://openalex.org/W2054902886","https://openalex.org/W2068197846","https://openalex.org/W2115167851","https://openalex.org/W2118420236","https://openalex.org/W2126105956","https://openalex.org/W2134042740","https://openalex.org/W2140142253","https://openalex.org/W2142311337","https://openalex.org/W2147555557","https://openalex.org/W2152448063","https://openalex.org/W2157380596","https://openalex.org/W2163801680","https://openalex.org/W2329673985","https://openalex.org/W2468317448","https://openalex.org/W2473954490","https://openalex.org/W2591222693","https://openalex.org/W2608822622","https://openalex.org/W2750760359","https://openalex.org/W2751297520","https://openalex.org/W2787740020","https://openalex.org/W2920866373","https://openalex.org/W2963097316","https://openalex.org/W2963406602","https://openalex.org/W2964285681","https://openalex.org/W3098269293","https://openalex.org/W6618372016","https://openalex.org/W6631190155","https://openalex.org/W6681045557","https://openalex.org/W6682588147","https://openalex.org/W6684073665","https://openalex.org/W6730191795","https://openalex.org/W6743582866","https://openalex.org/W6743833179"],"related_works":["https://openalex.org/W2038239089","https://openalex.org/W2376188964","https://openalex.org/W2110217619","https://openalex.org/W3111740253","https://openalex.org/W3115490882","https://openalex.org/W2033702946","https://openalex.org/W2980963561","https://openalex.org/W2902282441","https://openalex.org/W2380554435","https://openalex.org/W195918318"],"abstract_inverted_index":{"A":[0],"fusion":[1],"image":[2,32,37,48,74,119],"combining":[3],"both":[4],"anatomical":[5],"and":[6,22,34,50,89,124,144,156,162,167,179,195,228,230,264],"functional":[7],"information":[8],"obtained":[9,253],"by":[10],"registering":[11,91],"medical":[12,31],"images":[13],"of":[14,27,79,140,149,154,159,165,170,191,223,235,245],"two":[15,80],"different":[16],"modalities,":[17],"Positron":[18],"Emission":[19],"Tomography":[20,24],"(PET)":[21],"Computed":[23],"(CT),":[25],"is":[26,44,54,109],"great":[28],"significance":[29],"for":[30,70],"analysis":[33],"diagnosis.":[35],"Medical":[36],"registration":[38,53,120,133,207,249,275,288],"relies":[39],"on":[40,199],"similarity":[41,102],"measure":[42,103],"which":[43],"low":[45],"between":[46],"PET/CT":[47,52,73,246,287],"voxels":[49],"therefore":[51],"a":[55,100,106,122,125,238,242],"challenging":[56,285],"task.":[57,289],"To":[58],"address":[59],"this":[60,62,136],"issue,":[61],"paper":[63],"presents":[64],"an":[65],"unsupervised":[66],"end-to-end":[67],"method,":[68,215],"DenseRegNet,":[69,216],"deformable":[71,286],"3D":[72,84,92,96],"registration.":[75],"The":[76],"method":[77],"consists":[78],"stages:":[81],"(1)":[82],"predicting":[83],"displacement":[85],"vector":[86],"field":[87],"(DVF);":[88],"(2)":[90],"image.":[93],"In":[94,135],"the":[95,118,132,206,213,218,231,248,277,284],"DVF":[97],"prediction":[98],"stage,":[99,121],"two-level":[101],"together":[104],"with":[105,254,271],"deformation":[107],"regularization":[108],"proposed":[110,214,278],"as":[111,176],"loss":[112],"function":[113],"to":[114,130,204],"optimize":[115],"network":[116],"training.In":[117],"resampler":[123],"spatial":[126],"transformer":[127],"are":[128,173,202],"utilized":[129],"obtain":[131],"results.":[134,208],"paper,":[137],"663":[138],"pairs":[139,153,164],"Uptake":[141],"Value":[142],"(SUV)":[143],"Hounsfield":[145],"Unit":[146],"(Hu)":[147],"patches":[148,158,169],"106":[150],"patients,":[151],"227":[152],"SUV":[155,166],"Hu":[157,168],"35":[160,171],"patients":[161,172],"259":[163],"randomly":[174],"selected":[175],"training,":[177],"validation":[178],"test":[180],"set,":[181],"respectively.":[182],"Normalized":[183],"cross":[184],"correlation":[185],"(NCC),":[186],"intersection":[187],"over":[188],"union":[189],"(IoU)":[190],"liver":[192,224],"bounding":[193,225],"box":[194,226],"euclidean":[196],"distance":[197],"(ED)":[198],"landmark":[200],"points":[201],"used":[203],"evaluate":[205],"Experiment":[209],"results":[210,220,282],"show":[211],"that":[212],"achieves":[217,280],"best":[219],"in":[221,283],"terms":[222],"IoU":[227],"ED,":[229],"second":[232],"highest":[233],"value":[234],"NCC.":[236],"For":[237],"trained":[239],"model,":[240],"given":[241],"new":[243],"pair":[244],"images,":[247],"result":[250],"can":[251],"be":[252],"only":[255],"one":[256],"forward":[257],"calculation":[258],"within":[259],"10":[260],"seconds.":[261],"Through":[262],"qualitative":[263],"quantitative":[265],"analyses,":[266],"we":[267],"demonstrate":[268],"that,":[269],"compared":[270],"other":[272],"deep":[273],"learning":[274],"models,":[276],"DenseRegNet":[279],"improved":[281]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-19T21:40:30.786675","created_date":"2025-10-10T00:00:00"}
