{"id":"https://openalex.org/W7157013911","doi":"https://doi.org/10.48550/arxiv.2604.24524","title":"Point Cloud Registration for Fusion between SPECT MPI and CTA Images","display_name":"Point Cloud Registration for Fusion between SPECT MPI and CTA Images","publication_year":2026,"publication_date":"2026-04-27","ids":{"openalex":"https://openalex.org/W7157013911","doi":"https://doi.org/10.48550/arxiv.2604.24524"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.24524","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24524","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.24524","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134805041","display_name":"Ni Yao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Ni","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134787663","display_name":"Xiangyu Liu","orcid":"https://orcid.org/0000-0002-4625-4343"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xiangyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134774094","display_name":"Shaojie Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Shaojie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134817456","display_name":"Danyang Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Danyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134751772","display_name":"Chuang Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Chuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134813254","display_name":"Yanting Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yanting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048633477","display_name":"Jiaofen Nan","orcid":"https://orcid.org/0000-0001-6730-6977"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nan, Jiaofen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134767195","display_name":"Chengyang Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Chengyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134755385","display_name":"Fubao Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Fubao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134781780","display_name":"Chen Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134788054","display_name":"Zhihui Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Zhihui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134796025","display_name":"Weihua Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Weihua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":12,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.5105999708175659,"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"}},"topics":[{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.5105999708175659,"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/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.16750000417232513,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.16130000352859497,"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/point-cloud","display_name":"Point cloud","score":0.6069999933242798},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.5802000164985657},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5109000205993652},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.49140000343322754},{"id":"https://openalex.org/keywords/single-photon-emission-computed-tomography","display_name":"Single-photon emission computed tomography","score":0.4693000018596649},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.4090000092983246},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.38019999861717224},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.3700999915599823},{"id":"https://openalex.org/keywords/tomography","display_name":"Tomography","score":0.3528999984264374}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6438000202178955},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6069999933242798},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6010000109672546},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.5802000164985657},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5497000217437744},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5109000205993652},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.49140000343322754},{"id":"https://openalex.org/C2780441642","wikidata":"https://www.wikidata.org/wiki/Q849737","display_name":"Single-photon emission computed tomography","level":2,"score":0.4693000018596649},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.4090000092983246},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.38019999861717224},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3700999915599823},{"id":"https://openalex.org/C163716698","wikidata":"https://www.wikidata.org/wiki/Q841267","display_name":"Tomography","level":2,"score":0.3528999984264374},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.34369999170303345},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33239999413490295},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C2775842073","wikidata":"https://www.wikidata.org/wiki/Q208376","display_name":"Positron emission tomography","level":2,"score":0.3230000138282776},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3212999999523163},{"id":"https://openalex.org/C2778064278","wikidata":"https://www.wikidata.org/wiki/Q5372630","display_name":"Emission computed tomography","level":3,"score":0.3160000145435333},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.30630001425743103},{"id":"https://openalex.org/C2778405248","wikidata":"https://www.wikidata.org/wiki/Q1956679","display_name":"Myocardial perfusion imaging","level":3,"score":0.30070000886917114},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C2989005","wikidata":"https://www.wikidata.org/wiki/Q214963","display_name":"Nuclear medicine","level":1,"score":0.2851000130176544},{"id":"https://openalex.org/C2781347138","wikidata":"https://www.wikidata.org/wiki/Q1024492","display_name":"Computed tomography angiography","level":3,"score":0.28439998626708984},{"id":"https://openalex.org/C173974348","wikidata":"https://www.wikidata.org/wiki/Q1469893","display_name":"Fiducial marker","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2612000107765198},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C126795593","wikidata":"https://www.wikidata.org/wiki/Q7333813","display_name":"Rigid transformation","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.24524","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24524","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.24524","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.24524","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Clinical":[0],"fusion":[1,47],"of":[2,168,201,228,234],"Single":[3],"Photon":[4],"Emission":[5],"Computed":[6,14],"Tomography":[7,15],"Myocardial":[8],"Perfusion":[9],"Imaging":[10],"(SPECT":[11],"MPI)":[12],"and":[13,23,34,46,52,57,83,99,117,149,211,225],"Angiography":[16],"(CTA)":[17],"remains":[18],"limited":[19],"by":[20],"cross-modality":[21],"misregistration":[22],"reliance":[24],"on":[25,70,128,137],"manual":[26],"landmarks,":[27],"which":[28],"can":[29],"hinder":[30],"accurate":[31],"ischemia":[32,223],"localization":[33,224],"lesion-level":[35],"functional":[36,56,226],"assessment.":[37],"To":[38],"address":[39],"this":[40,129],"issue,":[41],"we":[42],"propose":[43],"a":[44,165,196,218],"registration":[45,120,133,238],"framework":[48,173],"for":[49,60,160,221],"SPECT":[50,74,184],"MPI":[51],"CTA":[53,179],"that":[54],"integrates":[55],"structural":[58],"information":[59],"comprehensive":[61],"cardiac":[62],"evaluation.":[63],"The":[64,151],"proposed":[65,172,215],"pipeline":[66],"performs":[67],"U-Net-based":[68],"segmentation":[69],"both":[71,95],"modalities.":[72],"On":[73,93],"MPI,":[75],"only":[76],"the":[77,110,171,187,192,214],"left":[78],"ventricle":[79],"(LV)":[80],"is":[81,103],"extracted,":[82],"anatomical":[84],"landmarks":[85,108],"are":[86,97,121,135,154],"automatically":[87,106],"derived":[88],"from":[89,178],"characteristic":[90],"LV":[91,138],"structures.":[92],"CTA,":[94],"ventricles":[96],"segmented,":[98],"their":[100],"spatial":[101],"relationship":[102],"used":[104],"to":[105,123,157],"define":[107],"at":[109],"interventricular":[111],"septal":[112],"junction.":[113],"Scale-space":[114],"consistency":[115],"preprocessing":[116],"landmark-driven":[118],"coarse":[119],"applied":[122],"mitigate":[124],"initial":[125],"misalignment.":[126],"Based":[127],"initialization,":[130,207],"multiple":[131],"fine":[132,209,237],"methods":[134],"evaluated":[136,188],"epicardial":[139],"surface":[140],"point":[141,198],"clouds,":[142],"including":[143],"ICP,":[144],"SICP,":[145],"CPD,":[146],"CluReg,":[147],"FFD,":[148],"BCPD-plus-plus.":[150],"resulting":[152],"transformations":[153],"then":[155],"propagated":[156],"voxel-level":[158,212],"resampling":[159],"high-precision":[161],"SPECT-CTA":[162],"fusion.":[163],"In":[164],"retrospective":[166],"cohort":[167],"60":[169],"patients,":[170],"preserved":[174],"sub-millimeter":[175],"coronary":[176,229],"detail":[177],"while":[180,231],"accurately":[181],"overlaying":[182],"quantitative":[183],"perfusion.":[185],"Among":[186],"methods,":[189],"BCPD-plus-plus":[190],"achieved":[191],"highest":[193],"accuracy":[194],"with":[195],"mean":[197],"cloud":[199],"distance":[200],"1.7":[202],"mm.":[203],"By":[204],"combining":[205],"robust":[206],"comparative":[208],"registration,":[210],"fusion,":[213],"approach":[216],"provides":[217],"practical":[219],"solution":[220],"myocardial":[222],"evaluation":[227],"lesions,":[230],"remaining":[232],"independent":[233],"any":[235],"specific":[236],"algorithm.":[239]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-29T00:00:00"}