{"id":"https://openalex.org/W7128521137","doi":"https://doi.org/10.48550/arxiv.2602.08717","title":"Zero-shot System for Automatic Body Region Detection for Volumetric CT and MR Images","display_name":"Zero-shot System for Automatic Body Region Detection for Volumetric CT and MR Images","publication_year":2026,"publication_date":"2026-02-09","ids":{"openalex":"https://openalex.org/W7128521137","doi":"https://doi.org/10.48550/arxiv.2602.08717"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.08717","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","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":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019681465","display_name":"Farnaz Khun Jush","orcid":"https://orcid.org/0000-0002-4860-1775"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jush, Farnaz Khun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024084156","display_name":"Grit Werner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Werner, Grit","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098682818","display_name":"Mark Klemens","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Klemens, Mark","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5075722670","display_name":"Matthias Lenga","orcid":"https://orcid.org/0000-0003-3771-2012"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lenga, Matthias","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5019681465"],"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.314300000667572,"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"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.314300000667572,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.20430000126361847,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.12300000339746475,"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/robustness","display_name":"Robustness (evolution)","score":0.6276000142097473},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5877000093460083},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.49390000104904175},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4697999954223633},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4302000105381012},{"id":"https://openalex.org/keywords/dicom","display_name":"DICOM","score":0.4291999936103821},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"Computed tomography","score":0.3490000069141388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7297999858856201},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6699000000953674},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6575999855995178},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6276000142097473},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5877000093460083},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.49390000104904175},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4697999954223633},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4302000105381012},{"id":"https://openalex.org/C77331912","wikidata":"https://www.wikidata.org/wiki/Q81095","display_name":"DICOM","level":2,"score":0.4291999936103821},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3325999975204468},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26759999990463257},{"id":"https://openalex.org/C3019060180","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automated method","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C3019831412","wikidata":"https://www.wikidata.org/wiki/Q5778278","display_name":"Fully automatic","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.08717","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.08717","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08717","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.08717","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reliable":[0],"identification":[1],"of":[2,144],"anatomical":[3,111,127],"body":[4,45],"regions":[5],"is":[6],"a":[7,58,80,90,102],"prerequisite":[8],"for":[9],"many":[10,36],"automated":[11],"medical":[12],"imaging":[13],"workflows,":[14],"yet":[15],"existing":[16],"solutions":[17,26],"remain":[18],"heavily":[19],"dependent":[20],"on":[21,117],"unreliable":[22],"DICOM":[23],"metadata.":[24],"Current":[25],"mainly":[27],"use":[28],"supervised":[29],"learning,":[30],"which":[31],"limits":[32],"their":[33],"applicability":[34],"in":[35,48,57,66,162],"real-world":[37],"scenarios.":[38],"In":[39],"this":[40],"work,":[41],"we":[42],"investigate":[43],"whether":[44],"region":[46,128],"detection":[47],"volumetric":[49],"CT":[50,120],"and":[51,73,100,121,137,147,154],"MR":[52,122],"images":[53],"can":[54],"be":[55],"achieved":[56],"fully":[59],"zero-shot":[60],"manner":[61],"by":[62,97],"using":[63],"knowledge":[64],"embedded":[65],"large":[67],"pre-trained":[68,85],"foundation":[69],"models.":[70],"We":[71],"propose":[72],"systematically":[74],"evaluate":[75],"three":[76],"training-free":[77],"pipelines:":[78],"(1)":[79],"segmentation-driven":[81,131],"rule-based":[82,132],"system":[83],"leveraging":[84],"multi-organ":[86],"segmentation":[87],"models,":[88],"(2)":[89],"Multimodal":[91],"Large":[92],"Language":[93],"Model":[94],"(MLLM)":[95],"guided":[96],"radiologist-defined":[98],"rules,":[99],"(3)":[101],"segmentation-aware":[103,168],"MLLM":[104,159,169],"that":[105],"combines":[106],"visual":[107],"input":[108],"with":[109,124,141],"explicit":[110],"evidence.":[112],"All":[113],"methods":[114],"are":[115],"evaluated":[116],"887":[118],"heterogeneous":[119],"scans":[123],"manually":[125],"verified":[126],"labels.":[129],"The":[130,158],"approach":[133],"achieves":[134],"the":[135,167],"strongest":[136],"most":[138],"consistent":[139],"performance,":[140],"weighted":[142],"F1-scores":[143],"0.947":[145],"(CT)":[146],"0.914":[148],"(MR),":[149],"demonstrating":[150],"robustness":[151],"across":[152],"modalities":[153],"atypical":[155],"scan":[156],"coverage.":[157],"performs":[160],"competitively":[161],"visually":[163],"distinctive":[164],"regions,":[165],"while":[166],"reveals":[170],"fundamental":[171],"limitations.":[172]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-11T00:00:00"}
