{"id":"https://openalex.org/W2782253125","doi":"https://doi.org/10.1109/isbi.2018.8363803","title":"Recovery of point clouds on surfaces: Application to image reconstruction","display_name":"Recovery of point clouds on surfaces: Application to image reconstruction","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2782253125","doi":"https://doi.org/10.1109/isbi.2018.8363803","mag":"2782253125","pmid":"https://pubmed.ncbi.nlm.nih.gov/33619441","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/7897514"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2018.8363803","doi":"https://doi.org/10.1109/isbi.2018.8363803","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363803","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"IEEE International Symposium on Biomedical Imaging (ISBI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7897514","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073618680","display_name":"Sunrita Poddar","orcid":"https://orcid.org/0000-0002-1853-6423","observed_orcids":["https://orcid.org/0000-0002-1853-6423","https://orcid.org/0009-0005-8456-6750"]},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sunrita Poddar","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Iowa, IA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Iowa, IA, USA","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072299998","display_name":"Mathews Jacob","orcid":"https://orcid.org/0000-0001-6196-3933","observed_orcids":["https://orcid.org/0000-0001-6196-3933"]},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mathews Jacob","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Iowa, IA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Iowa, IA, USA","institution_ids":["https://openalex.org/I126307644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I126307644"],"apc_list":null,"apc_paid":null,"fwci":2.1718,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.92510719,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":"51","issue":null,"first_page":"1272","last_page":"1275"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9336000084877014,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9336000084877014,"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/T11210","display_name":"Mathematical Analysis and Transform Methods","score":0.04390000179409981,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.00419999985024333,"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/smooth-surfaces","display_name":"smooth surfaces","score":0.7820000052452087},{"id":"https://openalex.org/keywords/bandlimited-functions","display_name":"band-limited functions","score":0.8830000162124634},{"id":"https://openalex.org/keywords/zero-level-set","display_name":"zero level set","score":0.7409999966621399},{"id":"https://openalex.org/keywords/exponential-map","display_name":"exponential map","score":0.9649999737739563},{"id":"https://openalex.org/keywords/nuclear-norm-minimization","display_name":"nuclear norm minimization","score":0.9789999723434448},{"id":"https://openalex.org/keywords/undersampled-measurements","display_name":"undersampled measurements","score":0.7720000147819519},{"id":"https://openalex.org/keywords/noisy-measurements","display_name":"noisy measurements","score":0.7689999938011169},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"curse of dimensionality","score":0.8389999866485596},{"id":"https://openalex.org/keywords/kernel-trick","display_name":"kernel trick","score":0.9990000128746033},{"id":"https://openalex.org/keywords/graph-signal-processing","display_name":"graph signal processing","score":0.9309999942779541},{"id":"https://openalex.org/keywords/cardiac-imaging","display_name":"cardiac imaging","score":0.6489999890327454},{"id":"https://openalex.org/keywords/free-breathing","display_name":"free breathing","score":0.7099999785423279},{"id":"https://openalex.org/keywords/dynamic-imaging","display_name":"dynamic imaging","score":0.7580000162124634}],"concepts":[{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6043681502342224},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5670447945594788},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5503360033035278},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5398895144462585},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.4946000277996063},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.45384615659713745},{"id":"https://openalex.org/C20885615","wikidata":"https://www.wikidata.org/wiki/Q825595","display_name":"Surface reconstruction","level":3,"score":0.4272058308124542},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.4127543568611145},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.3773818016052246},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3682594895362854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2910078465938568},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/isbi.2018.8363803","doi":"https://doi.org/10.1109/isbi.2018.8363803","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363803","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"IEEE International Symposium on Biomedical Imaging (ISBI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"},{"id":"pmid:33619441","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33619441","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE International Symposium on Biomedical Imaging","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:7897514","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7897514","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"},{"id":"pmh:oai:arXiv.org:1801.00886","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1801.00886","pdf_url":"https://arxiv.org/pdf/1801.00886","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,"listed_in":[],"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"},{"id":"mag:2782253125","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1801.00886.pdf","pdf_url":null,"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,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1801.00886","doi":"https://doi.org/10.48550/arxiv.1801.00886","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1801.00886","pdf_url":null,"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,"listed_in":[],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:7897514","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7897514","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G9000874707","display_name":"Novel Computational Framework for Free-Breathing & Ungated Dynamic MRI","funder_award_id":"R01EB019961","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"}],"funders":[{"id":"https://openalex.org/F4320337363","display_name":"National Institute of Biomedical Imaging and Bioengineering","ror":"https://ror.org/00372qc85"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2782253125.pdf","grobid_xml":"https://content.openalex.org/works/W2782253125.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W1991217933","https://openalex.org/W2032065978","https://openalex.org/W2044810215","https://openalex.org/W2072581947","https://openalex.org/W2196426102","https://openalex.org/W2211925052","https://openalex.org/W2225667838","https://openalex.org/W2397626289","https://openalex.org/W2622751099","https://openalex.org/W2726168645","https://openalex.org/W2741665069"],"related_works":["https://openalex.org/W2912009603","https://openalex.org/W1588616767","https://openalex.org/W2802090273","https://openalex.org/W2369206828","https://openalex.org/W2241769899","https://openalex.org/W7099606279","https://openalex.org/W2788537806","https://openalex.org/W2071678661","https://openalex.org/W2089202208","https://openalex.org/W2162841651"],"abstract_inverted_index":{"We":[0,21,34,58],"introduce":[1,87],"a":[2,10,31,54,117],"framework":[3,112,143],"for":[4],"the":[5,23,27,37,41,44,65,69,82,94,128,139],"recovery":[6],"of":[7,30,40,64,84,127,141],"points":[8,42,70],"on":[9,43,60],"smooth":[11],"surface":[12,24,45],"in":[13,53,106,130,144],"high-dimensional":[14],"space,":[15],"with":[16],"application":[17],"to":[18,25,67,102,121],"dynamic":[19],"imaging.":[20],"assume":[22],"be":[26,114],"zero-level":[28],"set":[29],"bandlimited":[32],"function.":[33],"show":[35],"that":[36,50,92],"exponential":[38],"maps":[39,66],"satisfy":[46],"annihilation":[47],"relations,":[48],"implying":[49],"they":[51],"lie":[52],"finite":[55],"dimensional":[56],"subspace.":[57],"rely":[59],"nuclear":[61],"norm":[62],"minimization":[63],"recover":[68],"from":[71,81],"noisy":[72],"and":[73,134],"undersampled":[74],"measurements.":[75],"Since":[76],"this":[77,111,142],"direct":[78],"approach":[79],"suffers":[80],"curse":[83],"dimensionality,":[85],"we":[86],"an":[88],"iterative":[89,103],"reweighted":[90],"algorithm":[91,99,129],"uses":[93],"\"kernel":[95],"trick\".":[96],"The":[97,125],"resulting":[98],"has":[100],"similarities":[101],"algorithms":[104],"used":[105],"graph":[107],"signal":[108],"processing":[109],"(GSP);":[110],"can":[113],"seen":[115],"as":[116],"continuous":[118],"domain":[119],"alternative":[120],"discrete":[122],"GSP":[123],"theory.":[124],"use":[126],"recovering":[131],"free":[132],"breathing":[133],"ungated":[135],"cardiac":[136],"data":[137],"shows":[138],"potential":[140],"practical":[145],"applications.":[146]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2018-01-12T00:00:00"}