{"id":"https://openalex.org/W3130324860","doi":"https://doi.org/10.1117/12.2580853","title":"Combined 3D super-resolution, de-noising and partial volume correction for percutaneous ablation","display_name":"Combined 3D super-resolution, de-noising and partial volume correction for percutaneous ablation","publication_year":2021,"publication_date":"2021-02-12","ids":{"openalex":"https://openalex.org/W3130324860","doi":"https://doi.org/10.1117/12.2580853","mag":"3130324860"},"language":"en","primary_location":{"id":"doi:10.1117/12.2580853","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2580853","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2021: Image Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://discovery.ucl.ac.uk/10116433/1/SISRSupp.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100615840","display_name":"Mark A. Pinnock","orcid":"https://orcid.org/0000-0001-7928-2458"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mark A. Pinnock","raw_affiliation_strings":["Univ. College London (United Kingdom)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. College London (United Kingdom)","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032309114","display_name":"Yipeng Hu","orcid":"https://orcid.org/0000-0003-4902-0486"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yipeng Hu","raw_affiliation_strings":["Univ. College London (United Kingdom)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. College London (United Kingdom)","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110688111","display_name":"Steve Bandula","orcid":null},"institutions":[{"id":"https://openalex.org/I1340918713","display_name":"University College London Hospitals NHS Foundation Trust","ror":"https://ror.org/042fqyp44","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I1340918713"]},{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Steve Bandula","raw_affiliation_strings":["Univ. College London (United Kingdom)","Univ. College London Hospitals NHS Foundation Trust (United Kingdom)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. College London (United Kingdom)","institution_ids":["https://openalex.org/I45129253"]},{"raw_affiliation_string":"Univ. College London Hospitals NHS Foundation Trust (United Kingdom)","institution_ids":["https://openalex.org/I1340918713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066703217","display_name":"Dean C. Barratt","orcid":"https://orcid.org/0000-0003-2916-655X"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dean C. Barratt","raw_affiliation_strings":["Univ. College London (United Kingdom)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. College London (United Kingdom)","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.01638454,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"39","last_page":"39"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.998199999332428,"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"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.998199999332428,"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/T11183","display_name":"Advanced X-ray Imaging Techniques","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9879000186920166,"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/interpolation","display_name":"Interpolation (computer graphics)","score":0.7079996466636658},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5776889324188232},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5384158492088318},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5020806789398193},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.49575909972190857},{"id":"https://openalex.org/keywords/oversampling","display_name":"Oversampling","score":0.4863074719905853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4619899392127991},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.43737921118736267},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36773693561553955},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33423560857772827},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.25339972972869873},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.16365638375282288}],"concepts":[{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.7079996466636658},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5776889324188232},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5384158492088318},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5020806789398193},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.49575909972190857},{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.4863074719905853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4619899392127991},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.43737921118736267},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36773693561553955},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33423560857772827},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25339972972869873},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.16365638375282288},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1117/12.2580853","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2580853","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2021: Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10116433","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10116433/","pdf_url":"https://discovery.ucl.ac.uk/10116433/1/SISRSupp.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"In: (Proceedings) SPIE Medical Imaging: Image Processing. International society for optics and photonics (2021) (In press).","raw_type":"Proceedings paper"}],"best_oa_location":{"id":"pmh:oai:eprints.ucl.ac.uk.OAI2:10116433","is_oa":true,"landing_page_url":"https://discovery.ucl.ac.uk/id/eprint/10116433/","pdf_url":"https://discovery.ucl.ac.uk/10116433/1/SISRSupp.pdf","source":{"id":"https://openalex.org/S4306400024","display_name":"UCL Discovery (University College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45129253","host_organization_name":"University College London","host_organization_lineage":["https://openalex.org/I45129253"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"In: (Proceedings) SPIE Medical Imaging: Image Processing. International society for optics and photonics (2021) (In press).","raw_type":"Proceedings paper"},"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3130324860.pdf","grobid_xml":"https://content.openalex.org/works/W3130324860.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W2026616100","https://openalex.org/W2069870105","https://openalex.org/W2165928415","https://openalex.org/W2271840356","https://openalex.org/W2464708700","https://openalex.org/W2766486317","https://openalex.org/W2789370848","https://openalex.org/W2885143776","https://openalex.org/W2952345581","https://openalex.org/W2963372104","https://openalex.org/W2997222478"],"related_works":["https://openalex.org/W2766503024","https://openalex.org/W4206637278","https://openalex.org/W4386005305","https://openalex.org/W3173198409","https://openalex.org/W3082051559","https://openalex.org/W1682621979","https://openalex.org/W2903618681","https://openalex.org/W3172259201","https://openalex.org/W3184937791","https://openalex.org/W2005223122"],"abstract_inverted_index":{"Percutaneous":[0],"cryoablation":[1],"is":[2,17,175],"becoming":[3],"more":[4],"popular":[5],"for":[6,20,34],"the":[7,66,98,116,136,173,177,223],"treatment":[8],"of":[9,213,215],"renal":[10],"cell":[11],"carcinoma.":[12],"Interventional":[13],"computed":[14],"tomography":[15],"(iCT)":[16],"commonly":[18],"used":[19,148],"guidance":[21],"but":[22,130],"reducing":[23,176],"radiation":[24],"dose":[25],"and":[26,48,61,70,94,106,120,127,162,168,205],"increasing":[27],"slice":[28,46,56],"thickness":[29],"makes":[30],"super-resolution":[31],"(SR)":[32],"essential":[33],"improving":[35],"image":[36],"quality.":[37],"The":[38,140],"proposed":[39],"method":[40],"takes":[41],"low":[42],"quality":[43,53],"(LQ),":[44],"thick":[45],"images":[47,57,73,102,157],"converts":[49],"them":[50],"to":[51,76,149,182,197],"high":[52],"(HQ),":[54],"thin":[55],"while":[58],"performing":[59],"denoising":[60],"partial":[62,179],"volume":[63,180],"correction":[64],"in":[65,211],"z-direction.":[67],"As":[68],"LQ":[69,91,100],"HQ":[71],"iCT":[72],"are":[74],"challenging":[75],"pair":[77],"up,":[78],"we":[79],"train":[80],"a":[81,144,183,193],"3D":[82],"U-Net":[83,117,155,174],"equipped":[84],"with":[85,103],"an":[86],"up-sampling":[87],"module":[88],"on":[89,97,113,135,154,200,208],"simulated":[90,201],"(sLQ)":[92],"data":[93,202,210,225],"then":[95],"test":[96],"real":[99,209],"(rLQ)":[101],"cubic":[104],"interpolation":[105,119,161,204],"random":[107,121,163,206],"forest":[108,122,164,207],"as":[109,220],"comparison.":[110],"During":[111],"validation":[112],"sLQ":[114],"data,":[115],"outperformed":[118],"(SSIM":[123],"0.9991":[124],"vs":[125],"0.9959":[126],"0.9985":[128],"respectively),":[129,170],"performance":[131],"suffered":[132],"when":[133,147],"testing":[134],"out-of-distribution":[137],"rLQ":[138],"images.":[139],"Dice":[141],"score":[142],"showed":[143],"substantial":[145],"improvement":[146],"compare":[150],"needle":[151],"segmentations":[152],"performed":[153],"generated":[156],"versus":[158],"those":[159],"from":[160],"(0.4073":[165],"vs.":[166],"0.2919":[167],"0.3777":[169],"indicating":[171],"that":[172,192],"z-direction":[178],"effect":[181],"greater":[184],"degree":[185],"than":[186],"these":[187],"techniques.":[188],"We":[189],"have":[190],"shown":[191],"neural":[194],"network":[195],"trained":[196],"perform":[198],"SR":[199],"outperforms":[203],"terms":[212],"localisation":[214],"clinically":[216],"relevant":[217],"objects":[218],"such":[219],"needles,":[221],"despite":[222],"differing":[224],"distribution.":[226]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
