{"id":"https://openalex.org/W4411599567","doi":"https://doi.org/10.1109/tro.2025.3582837","title":"LUDO: Low-Latency Understanding of Deformable Objects Using Point Cloud Occupancy Functions","display_name":"LUDO: Low-Latency Understanding of Deformable Objects Using Point Cloud Occupancy Functions","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411599567","doi":"https://doi.org/10.1109/tro.2025.3582837"},"language":"en","primary_location":{"id":"doi:10.1109/tro.2025.3582837","doi":"https://doi.org/10.1109/tro.2025.3582837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tro.2025.3582837","pdf_url":null,"source":{"id":"https://openalex.org/S144620930","display_name":"IEEE Transactions on Robotics","issn_l":"1552-3098","issn":["1552-3098","1546-1904","1941-0468"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["ccf-b","cwts-core","dongbi-a","jufo-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Robotics","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2411.08777","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067556504","display_name":"Pit Henrich","orcid":"https://orcid.org/0000-0002-4913-5040","observed_orcids":["https://orcid.org/0000-0002-4913-5040"]},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Pit Henrich","raw_affiliation_strings":["Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg, Erlangen, Germany","Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-4913-5040","affiliations":[{"raw_affiliation_string":"Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039110908","display_name":"Franziska Mathis-Ullrich","orcid":"https://orcid.org/0000-0001-5239-5305","observed_orcids":["https://orcid.org/0000-0001-5239-5305"]},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Franziska Mathis-Ullrich","raw_affiliation_strings":["Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg, Erlangen, Germany","Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg, Germany"],"raw_orcid":"https://orcid.org/0000-0001-5239-5305","affiliations":[{"raw_affiliation_string":"Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085474167","display_name":"Paul Maria Scheikl","orcid":"https://orcid.org/0000-0002-8079-1425","observed_orcids":["https://orcid.org/0000-0002-8079-1425"]},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Paul Maria Scheikl","raw_affiliation_strings":["Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg, Erlangen, Germany","Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg, Germany"],"raw_orcid":"https://orcid.org/0000-0002-8079-1425","affiliations":[{"raw_affiliation_string":"Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-University Erlangen-N&#x00FC;rnberg, Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09589515,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"41","issue":null,"first_page":"4283","last_page":"4299"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9922000169754028,"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":0.9922000169754028,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.005400000140070915,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10531","display_name":"Advanced Vision and Imaging","score":0.0006000000284984708,"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/robotic-biopsy","display_name":"robotic biopsy","score":0.6380000114440918},{"id":"https://openalex.org/keywords/uncertainty-estimation","display_name":"uncertainty estimation","score":0.8539999723434448},{"id":"https://openalex.org/keywords/explainability","display_name":"explainability","score":0.8539999723434448},{"id":"https://openalex.org/keywords/surgical-robotics","display_name":"surgical robotics","score":0.49000000953674316}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7106496691703796},{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.697847843170166},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6208573579788208},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5345726609230042},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5243240594863892},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43827494978904724},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4280218482017517},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20748290419578552},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.13495084643363953},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10075771808624268},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tro.2025.3582837","doi":"https://doi.org/10.1109/tro.2025.3582837","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tro.2025.3582837","pdf_url":null,"source":{"id":"https://openalex.org/S144620930","display_name":"IEEE Transactions on Robotics","issn_l":"1552-3098","issn":["1552-3098","1546-1904","1941-0468"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["ccf-b","cwts-core","dongbi-a","jufo-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Robotics","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2411.08777","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2411.08777","pdf_url":"https://arxiv.org/pdf/2411.08777","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":"doi:10.48550/arxiv.2411.08777","doi":"https://doi.org/10.48550/arxiv.2411.08777","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2411.08777","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":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2411.08777","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2411.08777","pdf_url":"https://arxiv.org/pdf/2411.08777","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"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"display_name":"Climate action","score":0.550000011920929,"id":"https://metadata.un.org/sdg/13"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2016959837","https://openalex.org/W2049981393","https://openalex.org/W2146990154","https://openalex.org/W2246023205","https://openalex.org/W2606462007","https://openalex.org/W2809199532","https://openalex.org/W2904383797","https://openalex.org/W2909750748","https://openalex.org/W2926629410","https://openalex.org/W2940581269","https://openalex.org/W2962858109","https://openalex.org/W3029115469","https://openalex.org/W3101609372","https://openalex.org/W3109585842","https://openalex.org/W3160041389","https://openalex.org/W3205146762","https://openalex.org/W4281488222","https://openalex.org/W4309676047","https://openalex.org/W4312578227","https://openalex.org/W4323914534","https://openalex.org/W4382999276","https://openalex.org/W4389352630","https://openalex.org/W4389665613","https://openalex.org/W4393241407","https://openalex.org/W4394593181","https://openalex.org/W4405785517","https://openalex.org/W4407737935","https://openalex.org/W6631190155","https://openalex.org/W6733905848","https://openalex.org/W6739778489","https://openalex.org/W6752823625","https://openalex.org/W6755308174"],"related_works":["https://openalex.org/W4282043467","https://openalex.org/W2105697914","https://openalex.org/W2202433167","https://openalex.org/W3093197249","https://openalex.org/W1540010871","https://openalex.org/W3023979140","https://openalex.org/W3177545769","https://openalex.org/W2904068067","https://openalex.org/W1565491139","https://openalex.org/W4297618682"],"abstract_inverted_index":{"Accurately":[0],"determining":[1],"the":[2,8,138,146],"shape":[3],"of":[4,10,36,105,111],"deformable":[5,37,115,143,149],"objects":[6,41,144],"and":[7,84,124,133],"location":[9],"their":[11,43,47],"internal":[12,48],"structures":[13],"is":[14],"crucial":[15],"for":[16,32,67,88,107,148],"medical":[17],"tasks":[18],"that":[19],"require":[20],"precise":[21],"targeting,":[22],"such":[23,91],"as":[24,92],"robotic":[25,99],"biopsies.":[26],"We":[27,94,117],"introduce":[28],"LUDO,":[29],"a":[30,51,102,121],"method":[31],"accurate":[33],"low-latency":[34],"understanding":[35],"objects.":[38,116],"LUDO":[39,63,96,119,136],"reconstructs":[40],"in":[42,56,78,97],"deformed":[44],"state,":[45],"including":[46],"structures,":[49],"from":[50],"single-view":[52],"point":[53],"cloud":[54],"observation":[55],"under":[57],"30":[58],"ms":[59],"using":[60],"occupancy":[61],"networks.":[62],"provides":[64,72],"uncertainty":[65,83],"estimates":[66],"its":[68,79,126],"predictions.":[69],"Additionally,":[70],"it":[71],"explainability":[73,85],"by":[74],"highlighting":[75],"key":[76],"features":[77],"input":[80],"observations.":[81],"Both":[82],"are":[86],"important":[87],"safety-critical":[89],"applications":[90],"surgery.":[93],"evaluate":[95],"real-world":[98],"experiments,":[100],"achieving":[101],"success":[103],"rate":[104],"98.9%":[106],"puncturing":[108],"various":[109],"regions":[110],"interest":[112],"(ROIs)":[113],"inside":[114],"compare":[118],"to":[120,140],"popular":[122],"baseline":[123],"show":[125],"superior":[127],"ROI":[128],"localization":[129],"accuracy,":[130],"training":[131],"time,":[132],"memory":[134],"requirements.":[135],"demonstrates":[137],"potential":[139],"interact":[141],"with":[142],"without":[145],"need":[147],"registration":[150],"methods.":[151]},"counts_by_year":[],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2025-10-10T00:00:00"}
