{"id":"https://openalex.org/W7155083593","doi":"https://doi.org/10.48550/arxiv.2604.17773","title":"Structure-Adaptive Sparse Diffusion in Voxel Space for 3D Medical Image Enhancement","display_name":"Structure-Adaptive Sparse Diffusion in Voxel Space for 3D Medical Image Enhancement","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7155083593","doi":"https://doi.org/10.48550/arxiv.2604.17773"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.17773","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17773","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.17773","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048928060","display_name":"Hongxu Jiang","orcid":"https://orcid.org/0000-0001-6633-6605"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jiang, Hongxu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134136362","display_name":"Fei Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Fei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006988090","display_name":"Boxiao Yu","orcid":"https://orcid.org/0000-0002-9857-789X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Boxiao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134205666","display_name":"Ying Zhang","orcid":"https://orcid.org/0000-0002-6517-9334"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Ying","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134129154","display_name":"Kaleb Smith","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Smith, Kaleb","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013691634","display_name":"Kuang Gong","orcid":"https://orcid.org/0000-0002-2669-2610"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gong, Kuang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5098824626","display_name":"Wei Shao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shao, Wei","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5048928060"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.6690999865531921,"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":0.6690999865531921,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.09870000183582306,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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":0.0763000026345253,"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/noise-reduction","display_name":"Noise reduction","score":0.7279000282287598},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.6290000081062317},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6050000190734863},{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.49810001254081726},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.49799999594688416},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4627000093460083},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4293999969959259},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42570000886917114},{"id":"https://openalex.org/keywords/non-local-means","display_name":"Non-local means","score":0.39629998803138733},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.388700008392334}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.7279000282287598},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6707000136375427},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.6290000081062317},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6078000068664551},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6050000190734863},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.49810001254081726},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.49799999594688416},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48829999566078186},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4627000093460083},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4293999969959259},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42570000886917114},{"id":"https://openalex.org/C101453961","wikidata":"https://www.wikidata.org/wiki/Q7048948","display_name":"Non-local means","level":4,"score":0.39629998803138733},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.388700008392334},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3871999979019165},{"id":"https://openalex.org/C149550507","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion MRI","level":3,"score":0.3776000142097473},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.37599998712539673},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3702000081539154},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36809998750686646},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.3443000018596649},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33899998664855957},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.3287000060081482},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2842000126838684},{"id":"https://openalex.org/C203504353","wikidata":"https://www.wikidata.org/wiki/Q4765461","display_name":"Anisotropic diffusion","level":3,"score":0.2750000059604645},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2709999978542328},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.2653000056743622},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.17773","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17773","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.17773","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17773","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5246325731277466,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Three-dimensional":[0],"(3D)":[1],"medical":[2,28],"image":[3],"enhancement,":[4,53],"including":[5],"denoising":[6,128,169],"and":[7,17,79,162,170],"super-resolution,":[8],"is":[9,175],"critical":[10],"for":[11,103],"clinical":[12],"diagnosis":[13],"in":[14,26,51,57,100,136],"CT,":[15,160],"PET,":[16,161],"MRI.":[18],"Although":[19],"diffusion":[20,42,75],"models":[21],"have":[22],"shown":[23],"remarkable":[24],"success":[25],"2D":[27],"imaging,":[29],"scaling":[30],"them":[31],"to":[32,40,151],"high-resolution":[33],"3D":[34],"volumes":[35],"remains":[36],"computationally":[37],"prohibitive":[38],"due":[39],"lengthy":[41],"trajectories":[43],"over":[44,129],"high-dimensional":[45],"volumetric":[46],"data.":[47],"We":[48],"observe":[49],"that":[50,77],"conditional":[52],"strong":[54],"anatomical":[55,124,143],"priors":[56],"the":[58,96,130],"degraded":[59],"input":[60],"render":[61],"dense":[62],"noise":[63],"schedules":[64],"largely":[65],"redundant.":[66],"Leveraging":[67],"this":[68],"insight,":[69],"we":[70],"propose":[71],"a":[72,82],"sparse":[73,132],"voxel-space":[74],"framework":[76,140],"trains":[78],"samples":[80],"on":[81,95,122,156,167],"compact":[83],"set":[84],"of":[85],"uniformly":[86],"subsampled":[87],"timesteps.":[88],"The":[89],"network":[90,119],"predicts":[91],"clean":[92],"data":[93,97],"directly":[94,135],"manifold,":[98],"supervised":[99],"velocity":[101],"space":[102],"stable":[104],"gradient":[105],"scaling.":[106],"A":[107],"lightweight":[108],"Structure-aware":[109],"Trajectory":[110],"Modulation":[111],"(STM)":[112],"module":[113],"recalibrates":[114],"time":[115],"embeddings":[116],"at":[117],"each":[118],"block":[120],"based":[121],"local":[123],"content,":[125],"enabling":[126],"structure-adaptive":[127],"shared":[131],"schedule.":[133],"Operating":[134],"voxel":[137],"space,":[138],"our":[139],"preserves":[141],"fine":[142],"detail":[144],"without":[145],"lossy":[146],"compression":[147],"while":[148],"achieving":[149],"up":[150],"$10\\times$":[152],"training":[153],"acceleration.":[154],"Experiments":[155],"four":[157],"datasets":[158],"spanning":[159],"MRI":[163],"demonstrate":[164],"state-of-the-art":[165],"performance":[166],"both":[168],"super-resolution":[171],"tasks.":[172],"Our":[173],"code":[174],"publicly":[176],"available":[177],"at:":[178],"https://github.com/mirthAI/sparse-3d-diffusion.":[179]},"counts_by_year":[],"updated_date":"2026-04-22T06:07:44.442478","created_date":"2026-04-22T00:00:00"}