{"id":"https://openalex.org/W4388208354","doi":"https://doi.org/10.1145/3604078.3604149","title":"Unsupervised Medical Image Registration via Dynamic Adaptive Total p-Variation Regularization","display_name":"Unsupervised Medical Image Registration via Dynamic Adaptive Total p-Variation Regularization","publication_year":2023,"publication_date":"2023-05-19","ids":{"openalex":"https://openalex.org/W4388208354","doi":"https://doi.org/10.1145/3604078.3604149"},"language":"en","primary_location":{"id":"doi:10.1145/3604078.3604149","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3604078.3604149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th International Conference on Digital Image Processing","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/A5009401684","display_name":"Ziqi Luo","orcid":"https://orcid.org/0009-0000-5908-4569"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziqi Luo","raw_affiliation_strings":["School of Medical Technology, Beijing Institute of Technology, China"],"raw_orcid":"https://orcid.org/0009-0000-5908-4569","affiliations":[{"raw_affiliation_string":"School of Medical Technology, Beijing Institute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101449662","display_name":"Dingkun Liu","orcid":"https://orcid.org/0000-0003-0268-3557"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingkun Liu","raw_affiliation_strings":["Laboratory of Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, China"],"raw_orcid":"https://orcid.org/0000-0003-0268-3557","affiliations":[{"raw_affiliation_string":"Laboratory of Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012390446","display_name":"Danni Ai","orcid":"https://orcid.org/0000-0002-2285-0570"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danni Ai","raw_affiliation_strings":["Laboratory of Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-2285-0570","affiliations":[{"raw_affiliation_string":"Laboratory of Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5009401684"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1375323,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9994000196456909,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9966999888420105,"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/classification-of-discontinuities","display_name":"Classification of discontinuities","score":0.797696590423584},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6565200090408325},{"id":"https://openalex.org/keywords/total-variation-denoising","display_name":"Total variation denoising","score":0.5625691413879395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5285441279411316},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5076431035995483},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.47537246346473694},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4579026699066162},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4502319097518921},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4481908679008484},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.4478665888309479},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.4450732469558716},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.2269306480884552},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12809985876083374}],"concepts":[{"id":"https://openalex.org/C15627037","wikidata":"https://www.wikidata.org/wiki/Q541961","display_name":"Classification of discontinuities","level":2,"score":0.797696590423584},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6565200090408325},{"id":"https://openalex.org/C207282899","wikidata":"https://www.wikidata.org/wiki/Q7828156","display_name":"Total variation denoising","level":3,"score":0.5625691413879395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5285441279411316},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5076431035995483},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.47537246346473694},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4579026699066162},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4502319097518921},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4481908679008484},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.4478665888309479},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.4450732469558716},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.2269306480884552},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12809985876083374}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3604078.3604149","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1145/3604078.3604149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th International Conference on Digital Image Processing","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/W1578985305","https://openalex.org/W1901129140","https://openalex.org/W1965921897","https://openalex.org/W1970928383","https://openalex.org/W2027804252","https://openalex.org/W2045484730","https://openalex.org/W2065319605","https://openalex.org/W2071989139","https://openalex.org/W2113576511","https://openalex.org/W2158167845","https://openalex.org/W2513186208","https://openalex.org/W2520815785","https://openalex.org/W3000249336","https://openalex.org/W3104164805","https://openalex.org/W3120640733","https://openalex.org/W3136762441","https://openalex.org/W3176521625","https://openalex.org/W3193216832","https://openalex.org/W3202718475","https://openalex.org/W3203698096","https://openalex.org/W4285242915"],"related_works":["https://openalex.org/W1972096828","https://openalex.org/W2529137940","https://openalex.org/W4302048708","https://openalex.org/W2359913921","https://openalex.org/W1595194509","https://openalex.org/W4239740410","https://openalex.org/W1996195943","https://openalex.org/W4205298958","https://openalex.org/W2486440955","https://openalex.org/W2038239089"],"abstract_inverted_index":{"The":[0,69,131],"sliding":[1,42,80,129,158],"motion":[2,8,19,81,159],"of":[3,14,17,34,78,97,107,115,123,140,157,163],"organ":[4,11,18,41,79],"edges":[5],"and":[6,76,89,120,150,161],"smooth":[7,28,148],"within":[9],"the":[10,15,32,37,62,74,83,92,95,113,116,121,124,128,141,166],"co-occur":[12],"because":[13],"complexity":[16],"during":[20,86],"respiration.":[21],"Many":[22],"registration":[23,66],"methods":[24],"assume":[25],"a":[26,49,137],"globally":[27],"deformation":[29,84,118,125,167],"field,":[30],"ignoring":[31],"problem":[33],"discontinuities":[35,164],"in":[36,155,165],"field":[38,85,119,126],"caused":[39],"by":[40],"motion.":[43],"In":[44],"this":[45],"paper,":[46],"we":[47],"propose":[48],"new":[50],"regularization":[51,149],"method":[52,133],"called":[53],"dynamic":[54],"adaptive":[55,152],"total":[56,153],"p-variance.":[57],"It":[58,143],"was":[59,134],"combined":[60],"with":[61],"unsupervised":[63],"deep":[64],"learning":[65],"framework":[67],"VoxelMorph.":[68],"proposed":[70,132],"approach":[71,101],"dynamically":[72],"estimates":[73],"position":[75],"magnitude":[77,93],"from":[82],"network":[87],"training":[88],"then":[90],"maps":[91],"to":[94,109],"p-values":[96],"Lp-norm":[98,108],"(1<p<2).":[99],"This":[100],"adaptively":[102],"assigns":[103],"different":[104],"exponential":[105],"values":[106],"each":[110],"voxel,":[111],"preserving":[112],"smoothness":[114],"internal":[117],"discontinuity":[122],"at":[127],"interface.":[130],"tested":[135],"on":[136],"4DCT":[138],"dataset":[139],"lung.":[142],"outperformed":[144],"other":[145],"methods,":[146],"including":[147],"locally":[151],"p-variation,":[154],"terms":[156],"correction":[160],"preservation":[162],"field.":[168]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
