{"id":"https://openalex.org/W7126096543","doi":"https://doi.org/10.1109/bibm66473.2025.11357090","title":"vHeatSR: Vision Model Based on Heat Conduction for Medical Image Super-Resolution","display_name":"vHeatSR: Vision Model Based on Heat Conduction for Medical Image Super-Resolution","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126096543","doi":"https://doi.org/10.1109/bibm66473.2025.11357090"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11357090","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357090","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"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/A5085136915","display_name":"Jingtao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingtao Zhang","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104073314","display_name":"Long Gao","orcid":"https://orcid.org/0009-0005-1261-4629"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Gao","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106237173","display_name":"Zhiqun Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqun Xiao","raw_affiliation_strings":["College of Computer Science and Technology, National University of Defense Technology,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, National University of Defense Technology,Changsha,China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.61713994,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7153","last_page":"7159"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.820900022983551,"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":0.820900022983551,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.05180000141263008,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.04259999841451645,"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/upsampling","display_name":"Upsampling","score":0.5666000247001648},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5457000136375427},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5101000070571899},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5091000199317932},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4571000039577484},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4442000091075897},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4429999887943268},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4307999908924103},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.37540000677108765}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7131999731063843},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5820000171661377},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.5666000247001648},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5497999787330627},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5457000136375427},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5101000070571899},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5091000199317932},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4571000039577484},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4442000091075897},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4429999887943268},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4307999908924103},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.37540000677108765},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.36730000376701355},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.35740000009536743},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.32120001316070557},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.32120001316070557},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C172100665","wikidata":"https://www.wikidata.org/wiki/Q7465774","display_name":"Thermal conduction","level":2,"score":0.30730000138282776},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2806999981403351},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11357090","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357090","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.750566840171814}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W1930824406","https://openalex.org/W2018342351","https://openalex.org/W2047920195","https://openalex.org/W2121927366","https://openalex.org/W2132848998","https://openalex.org/W2192954843","https://openalex.org/W2242218935","https://openalex.org/W2476548250","https://openalex.org/W2503339013","https://openalex.org/W2741137940","https://openalex.org/W2902874468","https://openalex.org/W2954930822","https://openalex.org/W2963372104","https://openalex.org/W3017083351","https://openalex.org/W3096739052","https://openalex.org/W3138516171","https://openalex.org/W3207918547","https://openalex.org/W4312933868","https://openalex.org/W4313447227","https://openalex.org/W4320900861","https://openalex.org/W4385245566","https://openalex.org/W4385800763","https://openalex.org/W4386083034","https://openalex.org/W4390872521","https://openalex.org/W4390872911","https://openalex.org/W4390970383","https://openalex.org/W4394625637","https://openalex.org/W4406260693","https://openalex.org/W4406271541","https://openalex.org/W4413145861"],"related_works":[],"abstract_inverted_index":{"Single":[0],"image":[1,58,161],"super-resolution":[2,59,141],"(SISR)":[3],"is":[4],"a":[5,53,74,81,87,91,105],"critical":[6],"task":[7],"in":[8,12,35,40,139],"computer":[9],"vision,":[10],"especially":[11],"medical":[13,57,129,147],"imaging,":[14],"where":[15],"high-resolution":[16,117],"data":[17],"can":[18],"significantly":[19],"influence":[20],"clinical":[21],"decisionmaking.":[22],"Recently,":[23],"physically":[24],"inspired":[25],"methods,":[26],"such":[27],"as":[28],"the":[29,109,116,134,150],"Heat":[30],"Conduction":[31],"Operator":[32],"(HCO)":[33],"introduced":[34],"vHeat,":[36],"have":[37],"shown":[38],"promise":[39],"modeling":[41,64,155],"spatial":[42],"correlations":[43],"within":[44],"visual":[45],"data.":[46],"In":[47],"this":[48],"work,":[49],"we":[50],"present":[51],"vHeatSR,":[52],"novel":[54],"framework":[55],"for":[56,159],"that":[60,79],"integrates":[61],"heat":[62],"conduction":[63],"with":[65,156],"frequency":[66],"domain.":[67],"Our":[68],"model":[69],"comprises":[70],"three":[71],"key":[72],"modules:":[73],"shallow":[75],"feature":[76,93],"extraction":[77,94],"module":[78,95,107],"includes":[80],"PixelShuffle-based":[82],"upsampling":[83],"layer":[84],"followed":[85],"by":[86],"discrete":[88,111],"wavelet":[89,112],"transform,":[90],"deep":[92],"composed":[96],"of":[97,101,136,152],"several":[98],"residual":[99],"blocks":[100],"vHeat's":[102],"HCO,":[103],"and":[104,127,143],"reconstruction":[106],"employing":[108],"inverse":[110],"transform":[113],"to":[114],"recover":[115],"image.":[118],"We":[119],"evaluate":[120],"vHeatSR":[121],"on":[122,146],"both":[123],"standard":[124],"benchmark":[125],"datasets":[126],"MRI":[128],"datasets.":[130],"Experimental":[131],"results":[132],"demonstrate":[133],"effectiveness":[135],"our":[137],"method":[138],"general":[140],"tasks":[142],"show":[144],"improvements":[145],"datasets,":[148],"highlighting":[149],"potential":[151],"integrating":[153],"physical":[154],"wavelet-based":[157],"representations":[158],"enhanced":[160],"reconstruction.":[162]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-01-30T00:00:00"}