{"id":"https://openalex.org/W7133352434","doi":"https://doi.org/10.48550/arxiv.2603.00887","title":"VEMamba: Efficient Isotropic Reconstruction of Volume Electron Microscopy with Axial-Lateral Consistent Mamba","display_name":"VEMamba: Efficient Isotropic Reconstruction of Volume Electron Microscopy with Axial-Lateral Consistent Mamba","publication_year":2026,"publication_date":"2026-03-01","ids":{"openalex":"https://openalex.org/W7133352434","doi":"https://doi.org/10.48550/arxiv.2603.00887"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.00887","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00887","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.2603.00887","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122857571","display_name":"Longmi Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Gao, Longmi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5016023400","display_name":"Pan Gao","orcid":"https://orcid.org/0000-0003-2768-8557"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Pan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5122857571"],"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/T10857","display_name":"Advanced Electron Microscopy Techniques and Applications","score":0.9144999980926514,"subfield":{"id":"https://openalex.org/subfields/1315","display_name":"Structural Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10857","display_name":"Advanced Electron Microscopy Techniques and Applications","score":0.9144999980926514,"subfield":{"id":"https://openalex.org/subfields/1315","display_name":"Structural Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12039","display_name":"Electron and X-Ray Spectroscopy Techniques","score":0.03750000149011612,"subfield":{"id":"https://openalex.org/subfields/2508","display_name":"Surfaces, Coatings and Films"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12404","display_name":"Mathematical Approximation and Integration","score":0.006200000178068876,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/isotropy","display_name":"Isotropy","score":0.7333999872207642},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6212000250816345},{"id":"https://openalex.org/keywords/anisotropy","display_name":"Anisotropy","score":0.6032000184059143},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5051000118255615},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.44020000100135803},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.37940001487731934},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.37529999017715454},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.35100001096725464},{"id":"https://openalex.org/keywords/tetrahedron","display_name":"Tetrahedron","score":0.34689998626708984}],"concepts":[{"id":"https://openalex.org/C184050105","wikidata":"https://www.wikidata.org/wiki/Q273163","display_name":"Isotropy","level":2,"score":0.7333999872207642},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6212000250816345},{"id":"https://openalex.org/C85725439","wikidata":"https://www.wikidata.org/wiki/Q466686","display_name":"Anisotropy","level":2,"score":0.6032000184059143},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5760999917984009},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5051000118255615},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47429999709129333},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.44020000100135803},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.39169999957084656},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.37529999017715454},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.35100001096725464},{"id":"https://openalex.org/C105239961","wikidata":"https://www.wikidata.org/wiki/Q160003","display_name":"Tetrahedron","level":2,"score":0.34689998626708984},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.3278999924659729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32580000162124634},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.30410000681877136},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.30090001225471497},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.2912999987602234},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C30769735","wikidata":"https://www.wikidata.org/wiki/Q2165951","display_name":"Volume rendering","level":3,"score":0.27480000257492065},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2736999988555908},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.26930001378059387},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26660001277923584},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.2535000145435333},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.00887","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00887","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.2603.00887","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00887","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Volume":[0],"Electron":[1],"Microscopy":[2],"(VEM)":[3],"is":[4,61,174],"crucial":[5],"for":[6,26,54,95,117,142],"3D":[7,64,84],"tissue":[8],"imaging":[9],"but":[10],"often":[11,29],"produces":[12],"anisotropic":[13,42,152],"data":[14],"with":[15],"poor":[16],"axial":[17,34,88],"resolution,":[18],"hindering":[19],"visualization":[20],"and":[21,36,89,103,128,150],"downstream":[22],"analysis.":[23],"Existing":[24],"methods":[25],"isotropic":[27,55],"reconstruction":[28],"suffer":[30],"from":[31],"neglecting":[32],"abundant":[33],"information":[35],"employing":[37],"simple":[38],"downsampling":[39],"to":[40,110,134],"simulate":[41],"data.":[43],"To":[44],"address":[45],"these":[46,113],"limitations,":[47],"we":[48,122],"propose":[49],"VEMamba,":[50],"an":[51,73],"efficient":[52,96],"framework":[53],"reconstruction.":[56,144],"The":[57,171],"core":[58],"of":[59],"VEMamba":[60,157],"a":[62,104,124,167],"novel":[63],"Dependency":[65],"Reordering":[66],"paradigm,":[67],"implemented":[68],"via":[69],"two":[70],"key":[71],"components:":[72],"Axial-Lateral":[74],"Chunking":[75],"Selective":[76],"Scan":[77],"Module":[78,108],"(ALCSSM),":[79],"which":[80],"intelligently":[81],"re-maps":[82],"complex":[83],"spatial":[85],"dependencies":[86],"(both":[87],"lateral)":[90],"into":[91,139],"optimized":[92],"1D":[93],"sequences":[94],"Mamba-based":[97],"modeling,":[98],"explicitly":[99],"enforcing":[100],"axial-lateral":[101],"consistency;":[102],"Dynamic":[105],"Weights":[106],"Aggregation":[107],"(DWAM)":[109],"adaptively":[111],"aggregate":[112],"reordered":[114],"sequence":[115],"outputs":[116],"enhanced":[118],"representational":[119],"power.":[120],"Furthermore,":[121],"introduce":[123],"realistic":[125],"degradation":[126],"simulation":[127],"then":[129],"leverage":[130],"Momentum":[131],"Contrast":[132],"(MoCo)":[133],"integrate":[135],"this":[136],"degradation-aware":[137],"knowledge":[138],"the":[140],"network":[141],"superior":[143],"Extensive":[145],"experiments":[146],"on":[147,176],"both":[148],"simulated":[149],"real-world":[151],"VEM":[153],"datasets":[154],"demonstrate":[155],"that":[156],"achieves":[158],"highly":[159],"competitive":[160],"performance":[161],"across":[162],"various":[163],"metrics":[164],"while":[165],"maintaining":[166],"lower":[168],"computational":[169],"footprint.":[170],"source":[172],"code":[173],"available":[175],"GitHub:":[177],"https://github.com/I2-Multimedia-Lab/VEMamba":[178]},"counts_by_year":[],"updated_date":"2026-03-04T07:09:34.246503","created_date":"2026-03-04T00:00:00"}