{"id":"https://openalex.org/W7171531351","doi":"https://doi.org/10.48550/arxiv.2607.23078","title":"Inverse Bayesian Inference for Extracting Lesion Dynamics from Longitudinal Spectral CT","display_name":"Inverse Bayesian Inference for Extracting Lesion Dynamics from Longitudinal Spectral CT","publication_year":2026,"publication_date":"2026-07-25","ids":{"openalex":"https://openalex.org/W7171531351","doi":"https://doi.org/10.48550/arxiv.2607.23078"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2607.23078","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2607.23078","pdf_url":"https://arxiv.org/pdf/2607.23078","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2607.23078","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115729138","display_name":"Lukas F\u00f6rner","orcid":"https://orcid.org/0009-0006-1656-6705","observed_orcids":["https://orcid.org/0009-0006-1656-6705"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"F\u00f6rner, Lukas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116974391","display_name":"Melina W\u00f6rdehoff","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"W\u00f6rdehoff, Melina","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143755438","display_name":"Julian Steffens","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2802007660","display_name":"University Hospital Augsburg","ror":"https://ror.org/03b0k9c14","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I2802007660"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Steffens, Julian","raw_affiliation_strings":["Dept. of diagnostic and interventional Radiology and Neuroradiology , University Hospital Augsburg , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of diagnostic and interventional Radiology and Neuroradiology , University Hospital Augsburg , Germany","institution_ids":["https://openalex.org/I2802007660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005651018","display_name":"Maximilian Schmutz","orcid":"https://orcid.org/0000-0002-7453-7260","observed_orcids":["https://orcid.org/0000-0002-7453-7260"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schmutz, Maximilian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067271311","display_name":"Rainer Claus","orcid":"https://orcid.org/0000-0003-2617-8766","observed_orcids":["https://orcid.org/0000-0003-2617-8766"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Claus, Rainer","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143751581","display_name":"Josua Decker","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2802007660","display_name":"University Hospital Augsburg","ror":"https://ror.org/03b0k9c14","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I2802007660"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Decker, Josua","raw_affiliation_strings":["Dept. of diagnostic and interventional Radiology and Neuroradiology , University Hospital Augsburg , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of diagnostic and interventional Radiology and Neuroradiology , University Hospital Augsburg , Germany","institution_ids":["https://openalex.org/I2802007660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071260048","display_name":"Thomas J. Kr\u00f6ncke","orcid":"https://orcid.org/0000-0003-4889-1036","observed_orcids":["https://orcid.org/0000-0003-4889-1036"]},"institutions":[{"id":"https://openalex.org/I2802007660","display_name":"University Hospital Augsburg","ror":"https://ror.org/03b0k9c14","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I2802007660"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kr\u00f6ncke, Thomas","raw_affiliation_strings":["Bavarian Center for Cancer Research (BZKF) Augsburg , Germany","Dept. of diagnostic and interventional Radiology and Neuroradiology , University Hospital Augsburg , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bavarian Center for Cancer Research (BZKF) Augsburg , Germany","institution_ids":[]},{"raw_affiliation_string":"Dept. of diagnostic and interventional Radiology and Neuroradiology , University Hospital Augsburg , Germany","institution_ids":["https://openalex.org/I2802007660"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057801204","display_name":"Kartikay Tehlan","orcid":"https://orcid.org/0000-0003-2417-1202","observed_orcids":["https://orcid.org/0000-0003-2417-1202"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tehlan, Kartikay","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5011729018","display_name":"Thomas Wendler","orcid":"https://orcid.org/0000-0002-0915-0510","observed_orcids":["https://orcid.org/0000-0002-0915-0510"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wendler, Thomas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.6259999871253967,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.6259999871253967,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.1851000040769577,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.14589999616146088,"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/tumor-growth-modeling","display_name":"tumor growth modeling","score":0.574999988079071},{"id":"https://openalex.org/keywords/metastasis","display_name":"metastasis","score":0.593999981880188},{"id":"https://openalex.org/keywords/non-small-cell-lung-cancer","display_name":"non-small cell lung cancer","score":0.8539999723434448},{"id":"https://openalex.org/keywords/liver-metastases","display_name":"liver metastasis","score":0.8320000171661377},{"id":"https://openalex.org/keywords/photon-counting-ct","display_name":"photon-counting CT","score":0.8370000123977661},{"id":"https://openalex.org/keywords/tumor-burden","display_name":"tumor burden","score":0.6209999918937683}],"concepts":[{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6312999725341797},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.590399980545044},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5673999786376953},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.5232999920845032},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5159000158309937},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5126000046730042},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.503000020980835},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4896000027656555},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.48339998722076416},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.43709999322891235},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4293999969959259},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.4065999984741211},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.374099999666214},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.328900009393692},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.3181999921798706},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.3100999891757965},{"id":"https://openalex.org/C2781156865","wikidata":"https://www.wikidata.org/wiki/Q827023","display_name":"Lesion","level":2,"score":0.3084000051021576},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C2983668108","wikidata":"https://www.wikidata.org/wiki/Q280453","display_name":"Spectral analysis","level":3,"score":0.2992999851703644},{"id":"https://openalex.org/C79379906","wikidata":"https://www.wikidata.org/wiki/Q3174497","display_name":"Dynamical systems theory","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2858000099658966},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.272599995136261},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.26660001277923584},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C23463724","wikidata":"https://www.wikidata.org/wiki/Q2308831","display_name":"Spectral method","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2607.23078","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2607.23078","pdf_url":"https://arxiv.org/pdf/2607.23078","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2607.23078","doi":"https://doi.org/10.48550/arxiv.2607.23078","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.23078","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2607.23078","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2607.23078","pdf_url":"https://arxiv.org/pdf/2607.23078","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.5683000087738037,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320331012","display_name":"Bayerische Staatsministerium f\u00fcr Wirtschaft, Landesentwicklung und Energie","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7171531351.pdf","grobid_xml":"https://content.openalex.org/works/W7171531351.grobid-xml"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W1868293759","https://openalex.org/W2019607817","https://openalex.org/W2103004421","https://openalex.org/W2121777917","https://openalex.org/W2149498546","https://openalex.org/W2572702041","https://openalex.org/W2763355946","https://openalex.org/W2889741596","https://openalex.org/W3110147920"],"related_works":["https://openalex.org/W7163811359","https://openalex.org/W4213264009","https://openalex.org/W2913592949","https://openalex.org/W7161123092","https://openalex.org/W7169845984","https://openalex.org/W2793709405","https://openalex.org/W3186932059","https://openalex.org/W3197820238","https://openalex.org/W7161798617","https://openalex.org/W7204082736"],"abstract_inverted_index":{"Longitudinal":[0],"medical":[1],"imaging":[2],"captures":[3,58,64,78],"temporal":[4],"evolution":[5,16,38],"of":[6,169],"lesions,":[7],"yet":[8],"extracting":[9,155],"the":[10,92],"underlying":[11],"dynamical":[12,103,148],"parameters":[13,157],"governing":[14],"this":[15],"remains":[17],"challenging.":[18],"We":[19,33,90],"propose":[20],"an":[21],"inverse":[22,147],"Bayesian":[23],"framework":[24,93],"for":[25,154],"inferring":[26],"lesion":[27,170],"dynamics":[28,60],"from":[29,99,158],"longitudinal":[30,159],"spectral":[31,35],"CT.":[32],"decompose":[34],"feature":[36,164],"($x$)":[37],"into":[39],"three":[40],"components:":[41],"\\begin{equation*}":[42],"\\frac{dx_i}{dt}":[43],"=":[44],"A_i":[45],"x_i":[46],"+":[47,51],"B":[48],"\\cdot":[49,53],"n":[50],"C":[52],"\u0394x_{\\text{sat}}":[54],"\\end{equation*}":[55],"where":[56],"$A_i$":[57],"intrinsic":[59],"(lesion-autonomous":[61],"evolution),":[62],"$B$":[63],"local":[65],"environment":[66],"tumour":[67,70],"burden":[68,71],"(organ":[69],"through":[72],"satellite":[73,109,122],"count":[74,110],"coupling),":[75],"and":[76,132,174],"$C$":[77],"environment/satellite":[79],"state":[80],"change":[81],"(i.e.,":[82],"whether":[83],"surrounding":[84],"lesions":[85,106,119],"move":[86],"similarly":[87],"or":[88],"not).":[89],"demonstrate":[91],"on":[94],"photon-counting":[95],"NSCLC":[96],"CT":[97],"data":[98,175],"metastases,":[100],"recovering":[101],"distinct":[102],"regimes:":[104],"lung":[105],"exhibit":[107],"significant":[108],"coupling":[111,124,141],"($B=-0.34$,":[112],"$p<0.05$)":[113],"suggesting":[114],"competitive":[115],"dynamics,":[116],"while":[117],"liver":[118],"show":[120],"synergistic":[121],"behaviour":[123],"($C\\approx+1.0$,":[125],"$p<0.05$).":[126],"Synthetic":[127],"validation":[128],"confirms":[129],"parameter":[130],"recovery,":[131],"cross-coupling":[133],"analysis":[134],"validates":[135],"that":[136],"our":[137],"method":[138],"detects":[139],"non-zero":[140],"when":[142],"present.":[143],"This":[144],"work":[145],"establishes":[146],"inference":[149],"as":[150],"a":[151],"principled":[152],"methodology":[153],"interpretable":[156],"imaging,":[160],"moving":[161],"beyond":[162],"static":[163],"extraction":[165],"toward":[166],"mechanistic":[167],"characterisation":[168],"behaviour.":[171],"The":[172],"code":[173],"are":[176],"available":[177],"at:":[178],"https://github.com/lukasf98/inverse-bayesian-inference":[179]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-07-29T00:00:00"}
