{"id":"https://openalex.org/W7126025608","doi":"https://doi.org/10.1109/bibm66473.2025.11357130","title":"A Survey of Medical Point Cloud Shape Learning: Registration, Reconstruction and Variation","display_name":"A Survey of Medical Point Cloud Shape Learning: Registration, Reconstruction and Variation","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126025608","doi":"https://doi.org/10.1109/bibm66473.2025.11357130"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11357130","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357130","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2508.03057","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007079241","display_name":"Tongxu Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongxu Zhang","raw_affiliation_strings":["East China University of Science and Technology,Xuhui,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China University of Science and Technology,Xuhui,Shanghai,China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124221706","display_name":"Zhiming Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiming Liang","raw_affiliation_strings":["East China University of Science and Technology,Xuhui,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China University of Science and Technology,Xuhui,Shanghai,China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124271148","display_name":"Bei Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bei Wang","raw_affiliation_strings":["East China University of Science and Technology,Xuhui,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China University of Science and Technology,Xuhui,Shanghai,China","institution_ids":["https://openalex.org/I143593769"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I143593769"],"apc_list":null,"apc_paid":null,"fwci":11.992,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.98823844,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5777","last_page":"5782"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.8129000067710876,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.8129000067710876,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.030799999833106995,"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":0.023399999365210533,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7802000045776367},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5383999943733215},{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.5221999883651733},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46399998664855957},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.4478999972343445},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4205000102519989},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.36419999599456787}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7802000045776367},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5534999966621399},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5383999943733215},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.5221999883651733},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5084999799728394},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46399998664855957},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.4478999972343445},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4291999936103821},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.36419999599456787},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3571999967098236},{"id":"https://openalex.org/C106977388","wikidata":"https://www.wikidata.org/wiki/Q2752427","display_name":"Medical research","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34599998593330383},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.32839998602867126},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32109999656677246},{"id":"https://openalex.org/C118317068","wikidata":"https://www.wikidata.org/wiki/Q2100760","display_name":"Point distribution model","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.25839999318122864}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bibm66473.2025.11357130","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357130","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2508.03057","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.03057","pdf_url":"https://arxiv.org/pdf/2508.03057","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2508.03057","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.03057","pdf_url":"https://arxiv.org/pdf/2508.03057","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1980354067","https://openalex.org/W2141619730","https://openalex.org/W2158167845","https://openalex.org/W2258978862","https://openalex.org/W2418621285","https://openalex.org/W2464708700","https://openalex.org/W2945064798","https://openalex.org/W2979750740","https://openalex.org/W3035168834","https://openalex.org/W3039448353","https://openalex.org/W3083622693","https://openalex.org/W3092480895","https://openalex.org/W3118615836","https://openalex.org/W3163400780","https://openalex.org/W3173232438","https://openalex.org/W3200745935","https://openalex.org/W3201155976","https://openalex.org/W3203630346","https://openalex.org/W3206487194","https://openalex.org/W3210000514","https://openalex.org/W4212923172","https://openalex.org/W4214755140","https://openalex.org/W4224942324","https://openalex.org/W4283269971","https://openalex.org/W4285235575","https://openalex.org/W4318213692","https://openalex.org/W4319299898","https://openalex.org/W4372337834","https://openalex.org/W4386699379","https://openalex.org/W4387211052","https://openalex.org/W4387211200","https://openalex.org/W4387211471","https://openalex.org/W4387211641","https://openalex.org/W4387666018","https://openalex.org/W4387667085","https://openalex.org/W4388145420","https://openalex.org/W4390673946","https://openalex.org/W4390971171","https://openalex.org/W4391331113","https://openalex.org/W4392741075","https://openalex.org/W4394994634","https://openalex.org/W4401016768","https://openalex.org/W4401930702","https://openalex.org/W4402716402","https://openalex.org/W4402920676","https://openalex.org/W4403139320","https://openalex.org/W4403213329","https://openalex.org/W4403757203","https://openalex.org/W4403757212","https://openalex.org/W4405873576","https://openalex.org/W4406260502","https://openalex.org/W4410737588","https://openalex.org/W4410838785","https://openalex.org/W4414367651","https://openalex.org/W4416750967"],"related_works":[],"abstract_inverted_index":{"Point":[0],"clouds":[1],"have":[2,28],"become":[3],"an":[4],"increasingly":[5],"important":[6],"representation":[7],"for":[8,56,124,129,137],"3D":[9],"medical":[10,57,94,144],"imaging,":[11],"offering":[12],"a":[13,47],"compact,":[14],"surface-preserving":[15],"alternative":[16],"to":[17,76],"traditional":[18],"voxel":[19],"or":[20],"mesh-based":[21],"approaches.":[22],"Recent":[23],"advances":[24],"in":[25,32,92,143],"deep":[26],"learning":[27,142],"enabled":[29],"rapid":[30],"progress":[31],"extracting,":[33],"modeling,":[34],"and":[35,49,67,82,85,89,107,121,126],"analyzing":[36],"anatomical":[37],"shapes":[38],"directly":[39],"from":[40,74],"point":[41,58,139],"cloud":[42],"data.":[43],"This":[44],"paper":[45],"provides":[46],"comprehensive":[48],"systematic":[50],"survey":[51],"of":[52,101],"learning-based":[53],"shape":[54,141],"analysis":[55],"clouds,":[59],"focusing":[60],"on":[61],"three":[62],"fundamental":[63],"tasks:":[64],"registration,":[65],"reconstruction,":[66],"variation":[68],"modeling.":[69],"We":[70,110],"review":[71],"recent":[72],"literature":[73],"2021":[75],"2025,":[77],"summarize":[78],"representative":[79],"methods,":[80],"datasets,":[81],"evaluation":[83],"metrics,":[84],"highlight":[86],"clinical":[87,130],"applications":[88],"unique":[90],"challenges":[91],"the":[93,99,122],"domain.":[95],"Key":[96],"trends":[97],"include":[98],"integration":[100],"hybrid":[102],"representations,":[103],"large-scale":[104],"self-supervised":[105],"models,":[106],"generative":[108],"techniques.":[109],"also":[111],"discuss":[112],"current":[113],"limitations,":[114],"such":[115],"as":[116],"data":[117],"scarcity,":[118],"inter-patient":[119],"variability,":[120],"need":[123],"interpretable":[125],"robust":[127],"solutions":[128],"deployment.":[131],"Finally,":[132],"future":[133],"directions":[134],"are":[135],"outlined":[136],"advancing":[138],"cloud-based":[140],"imaging.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":4}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2026-01-30T00:00:00"}
