{"id":"https://openalex.org/W7117563261","doi":"https://doi.org/10.1109/tmi.2025.3648299","title":"NeeCo: Image Synthesis of Novel Instrument States Based on Dynamic and Deformable 3-D Gaussian Reconstruction","display_name":"NeeCo: Image Synthesis of Novel Instrument States Based on Dynamic and Deformable 3-D Gaussian Reconstruction","publication_year":2025,"publication_date":"2025-12-30","ids":{"openalex":"https://openalex.org/W7117563261","doi":"https://doi.org/10.1109/tmi.2025.3648299","pmid":"https://pubmed.ncbi.nlm.nih.gov/41468333"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2025.3648299","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2025.3648299","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5121583516","display_name":"Tianle Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tianle Zeng","raw_affiliation_strings":["School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K"],"raw_orcid":"https://orcid.org/0009-0004-1659-6643","affiliations":[{"raw_affiliation_string":"School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121535385","display_name":"Junlei Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Junlei Hu","raw_affiliation_strings":["School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K"],"raw_orcid":"https://orcid.org/0000-0001-7394-5580","affiliations":[{"raw_affiliation_string":"School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107580545","display_name":"Gerardo Loza Galindo","orcid":null},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gerardo Loza Galindo","raw_affiliation_strings":["School of Computer Science, University of Leeds, Leeds, U.K"],"raw_orcid":"https://orcid.org/0000-0003-2841-0506","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Leeds, Leeds, U.K","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080765299","display_name":"Sharib Ali","orcid":"https://orcid.org/0000-0003-1313-3542"},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sharib Ali","raw_affiliation_strings":["School of Computer Science, University of Leeds, Leeds, U.K"],"raw_orcid":"https://orcid.org/0000-0003-1313-3542","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Leeds, Leeds, U.K","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121525166","display_name":"Duygu Sarikaya","orcid":null},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Duygu Sarikaya","raw_affiliation_strings":["School of Computer Science, University of Leeds, Leeds, U.K"],"raw_orcid":"https://orcid.org/0000-0002-2083-4999","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Leeds, Leeds, U.K","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035357710","display_name":"Pietro Valdastri","orcid":"https://orcid.org/0000-0002-2280-5438"},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Pietro Valdastri","raw_affiliation_strings":["School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K"],"raw_orcid":"https://orcid.org/0000-0002-2280-5438","affiliations":[{"raw_affiliation_string":"School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121593625","display_name":"Dominic Jones","orcid":null},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dominic Jones","raw_affiliation_strings":["School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K"],"raw_orcid":"https://orcid.org/0000-0002-2961-8483","affiliations":[{"raw_affiliation_string":"School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K","institution_ids":["https://openalex.org/I130828816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130828816"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.66756415,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"45","issue":"5","first_page":"2100","last_page":"2112"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10916","display_name":"Surgical Simulation and Training","score":0.25839999318122864,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T10916","display_name":"Surgical Simulation and Training","score":0.25839999318122864,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.14509999752044678,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.06939999759197235,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5985000133514404},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.5091000199317932},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.47749999165534973},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4244999885559082},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.40139999985694885},{"id":"https://openalex.org/keywords/gaussian-network-model","display_name":"Gaussian network model","score":0.3765000104904175},{"id":"https://openalex.org/keywords/gaussian-blur","display_name":"Gaussian blur","score":0.37560001015663147},{"id":"https://openalex.org/keywords/viewpoints","display_name":"Viewpoints","score":0.35920000076293945},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.3472999930381775}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8079000115394592},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7962999939918518},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7315999865531921},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5985000133514404},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5091000199317932},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.47749999165534973},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4244999885559082},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.40139999985694885},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.3765000104904175},{"id":"https://openalex.org/C104317376","wikidata":"https://www.wikidata.org/wiki/Q1894545","display_name":"Gaussian blur","level":5,"score":0.37560001015663147},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3472999930381775},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3352000117301941},{"id":"https://openalex.org/C173552908","wikidata":"https://www.wikidata.org/wiki/Q1366289","display_name":"Graphics pipeline","level":4,"score":0.3285999894142151},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C65892221","wikidata":"https://www.wikidata.org/wiki/Q1113935","display_name":"Gaussian filter","level":3,"score":0.274399995803833},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.2671000063419342},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.2551000118255615},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.2529999911785126},{"id":"https://openalex.org/C194969405","wikidata":"https://www.wikidata.org/wiki/Q170519","display_name":"Virtual reality","level":2,"score":0.25130000710487366}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013552","descriptor_name":"Swine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013552","descriptor_name":"Swine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D021621","descriptor_name":"Imaging, Three-Dimensional","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D021621","descriptor_name":"Imaging, Three-Dimensional","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2025.3648299","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2025.3648299","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Medical Imaging","raw_type":"journal-article"},{"id":"pmid:41468333","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41468333","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,"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":"IEEE transactions on medical imaging","raw_type":null}],"best_oa_location":null,"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":{"Computer":[0],"vision-based":[1],"technologies":[2],"significantly":[3],"enhance":[4],"surgical":[5,41,53,59],"automation":[6],"by":[7,81,198,210,220],"advancing":[8],"tool":[9,111,116],"tracking,":[10],"detection,":[11],"and":[12,64,112,115,176],"localization.":[13],"However,":[14],"Current":[15],"data-driven":[16],"approaches":[17],"are":[18],"data-voracious,":[19],"requiring":[20],"large,":[21],"high-quality":[22],"labeled":[23,156],"image":[24,42,146,157,183],"datasets.":[25,43],"Our":[26,185],"Work":[27],"introduces":[28],"a":[29,46,72,101,120],"novel":[30],"dynamic":[31,47,52,73],"Gaussian":[32,48],"Splatting":[33],"technique":[34],"to":[35,50,77,213],"address":[36,78],"the":[37,56,133,137,160,167,189,199],"data":[38,208],"scarcity":[39],"in":[40,217],"We":[44,70,164],"propose":[45],"model":[49,218],"represent":[51],"scenes,":[54],"enabling":[55],"rendering":[57],"of":[58,110,122,144,169,191],"instruments":[60],"from":[61,86,136],"unseen":[62,181],"viewpoints":[63],"deformations":[65],"with":[66,107,119,159,205],"real":[67,175],"tissue":[68],"backgrounds.":[69],"utilize":[71],"training":[74],"adjustment":[75],"strategy":[76],"challenges":[79],"posed":[80],"poorly":[82],"calibrated":[83],"camera":[84,113],"poses":[85],"real-world":[87,182],"scenarios.":[88],"Additionally,":[89],"automatically":[90],"generate":[91],"annotations":[92],"for":[93],"our":[94,152],"synthetic":[95,145,177,195],"data.":[96],"For":[97],"evaluation,":[98],"we":[99,130],"constructed":[100],"new":[102],"dataset":[103],"featuring":[104],"seven":[105],"scenes":[106],"14,000":[108],"frames":[109],"motion":[114],"jaw":[117],"articulation,":[118],"background":[121],"an":[123,180,214],"ex-vivo":[124],"porcine":[125],"model.":[126],"Using":[127],"this":[128],"dataset,":[129],"synthetically":[131],"replicate":[132],"scene":[134],"deformation":[135],"ground":[138],"truth":[139],"data,":[140],"allowing":[141],"direct":[142],"comparisons":[143],"quality.":[147],"Experimental":[148],"results":[149,186],"illustrate":[150],"that":[151,188],"method":[153,201],"generates":[154],"photo-realistic":[155],"datasets":[158],"highest":[161],"PSNR":[162],"(29.87).":[163],"further":[165],"evaluate":[166],"performance":[168,190],"medical-specific":[170],"neural":[171],"networks":[172],"trained":[173,193,204],"on":[174,194],"images":[178,196],"using":[179],"dataset.":[184],"show":[187],"models":[192],"generated":[197],"proposed":[200],"outperforms":[202],"those":[203],"state-of-the-art":[206],"standard":[207],"augmentation":[209],"10%,":[211],"leading":[212],"overall":[215],"improvement":[216],"performances":[219],"nearly":[221],"15%.":[222]},"counts_by_year":[],"updated_date":"2026-05-08T13:12:06.581006","created_date":"2025-12-30T00:00:00"}
