{"id":"https://openalex.org/W7165626655","doi":"https://doi.org/10.48550/arxiv.2606.20703","title":"Robust Image-Driven Phenotyping of Ovarian Tumor Cells using Optimized Dynamic Features in Hyperbolic Channels","display_name":"Robust Image-Driven Phenotyping of Ovarian Tumor Cells using Optimized Dynamic Features in Hyperbolic Channels","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7165626655","doi":"https://doi.org/10.48550/arxiv.2606.20703"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.20703","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20703","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,"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.20703","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139205429","display_name":"Hong-Fei Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Hong-Fei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103668258","display_name":"Gao X","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Xi-Lin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039420617","display_name":"Y. Xiang","orcid":"https://orcid.org/0000-0002-9423-4865"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiang, Yi-Juan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043900893","display_name":"Sicong Huang","orcid":"https://orcid.org/0000-0003-0854-4734"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Shu-Song","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139134824","display_name":"Yi-lin Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yi-lin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074825899","display_name":"Chun\u2010Dong Xue","orcid":"https://orcid.org/0000-0002-5259-4491"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Chun-Dong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139198231","display_name":"Zhuo Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zhuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103280126","display_name":"Yong\u2010Jiang Li","orcid":"https://orcid.org/0000-0002-4678-9209"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yong-Jiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5006205597","display_name":"Xu-Qu Hu","orcid":"https://orcid.org/0000-0001-5606-137X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Xu-Qu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"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/T10379","display_name":"Cellular Mechanics and Interactions","score":0.36000001430511475,"subfield":{"id":"https://openalex.org/subfields/1307","display_name":"Cell 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/T10379","display_name":"Cellular Mechanics and Interactions","score":0.36000001430511475,"subfield":{"id":"https://openalex.org/subfields/1307","display_name":"Cell 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/T12859","display_name":"Cell Image Analysis Techniques","score":0.10750000178813934,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/T11190","display_name":"3D Printing in Biomedical Research","score":0.08179999887943268,"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/feature","display_name":"Feature (linguistics)","score":0.6793000102043152},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5692999958992004},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5662000179290771},{"id":"https://openalex.org/keywords/subtyping","display_name":"Subtyping","score":0.5177000164985657},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.504800021648407},{"id":"https://openalex.org/keywords/binary-independence-model","display_name":"Binary Independence Model","score":0.49320000410079956},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4812999963760376},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47859999537467957},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4708000123500824}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6793000102043152},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5692999958992004},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5662000179290771},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5404999852180481},{"id":"https://openalex.org/C83852419","wikidata":"https://www.wikidata.org/wiki/Q2713292","display_name":"Subtyping","level":2,"score":0.5177000164985657},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.504800021648407},{"id":"https://openalex.org/C37061001","wikidata":"https://www.wikidata.org/wiki/Q3531721","display_name":"Binary Independence Model","level":3,"score":0.49320000410079956},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4812999963760376},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47859999537467957},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.47099998593330383},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4708000123500824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46219998598098755},{"id":"https://openalex.org/C8673954","wikidata":"https://www.wikidata.org/wiki/Q138845","display_name":"Microfluidics","level":2,"score":0.4223000109195709},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.358599990606308},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.35179999470710754},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.3476000130176544},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.3206999897956848},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3138999938964844},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30979999899864197},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C35527583","wikidata":"https://www.wikidata.org/wiki/Q189156","display_name":"Cellular automaton","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.27399998903274536},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.26260000467300415},{"id":"https://openalex.org/C8171440","wikidata":"https://www.wikidata.org/wiki/Q903414","display_name":"Steady state (chemistry)","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2606000006198883},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C2778744346","wikidata":"https://www.wikidata.org/wiki/Q1152224","display_name":"Distinctive feature","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.20703","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20703","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,"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.20703","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20703","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,"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"},"sustainable_development_goals":[{"score":0.7612539529800415,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Label-free,":[0],"image-based":[1],"cellular":[2],"mechanophenotyping":[3],"in":[4,134,144],"microfluidic":[5],"devices":[6],"provides":[7],"a":[8,62,91,96,186],"high-throughput":[9],"method":[10],"for":[11,116,120,190],"single-cell":[12],"profiling.":[13],"However,":[14],"while":[15,160],"complex":[16],"microchannels":[17],"(e.g.,":[18],"hyperbolic":[19],"geometries)":[20],"reveal":[21],"transient":[22],"deformation":[23],"dynamics":[24],"under":[25],"continuous":[26,191],"extensional":[27],"stress,":[28],"the":[29,76,126,135,145],"resulting":[30],"high-dimensional":[31],"feature":[32,48,93],"spaces":[33],"are":[34],"highly":[35],"susceptible":[36],"to":[37,50,89,142],"hydrodynamic":[38],"artifacts.":[39],"Flow":[40],"rate":[41],"variations":[42],"often":[43],"distort":[44],"discriminative":[45],"boundaries,":[46],"linking":[47],"distributions":[49],"fluid":[51],"conditions":[52],"rather":[53],"than":[54],"intrinsic":[55],"biology.":[56],"To":[57],"overcome":[58],"this,":[59],"we":[60,107],"introduce":[61],"stability-guided":[63],"analytical":[64],"framework":[65,184],"that":[66,151],"decouples":[67],"flow-induced":[68],"noise":[69],"from":[70,140],"authentic":[71],"mechanobiological":[72],"signatures.":[73],"We":[74,148],"tracked":[75],"morphodynamic,":[77],"kinematic,":[78],"and":[79,85,104,179],"intracellular":[80,165],"optical-density":[81],"trajectories":[82],"of":[83,128],"healthy":[84],"malignant":[86],"ovarian":[87],"cells":[88],"build":[90],"93-dimensional":[92],"space.":[94],"Using":[95],"cross-flow":[97],"screening":[98],"strategy":[99],"based":[100],"on":[101,156],"structural":[102],"consistency":[103],"statistical":[105],"persistence,":[106],"isolated":[108],"robust":[109],"descriptors,":[110],"creating":[111],"task-adapted":[112],"subsets":[113,170],"(20":[114],"features":[115],"binary":[117,153],"classification;":[118],"25":[119],"cancer":[121],"subtyping).":[122],"Variance-attribution":[123],"analysis":[124],"confirmed":[125],"neutralization":[127],"flow-conditioned":[129],"artifacts;":[130],"notably,":[131],"flow-associated":[132],"variance":[133],"primary":[136],"principal":[137],"component":[138],"fell":[139],"69.9%":[141],"9.3%":[143],"subtyping":[146,162],"task.":[147],"also":[149],"found":[150],"macroscopic":[152],"discrimination":[154],"depends":[155],"bulk":[157],"kinematic":[158],"transitions,":[159],"clonal":[161],"requires":[163],"localized":[164],"optical":[166],"heterogeneity.":[167],"These":[168],"optimized":[169],"maintained":[171],"diagnostic":[172],"fidelity":[173],"across":[174],"multiple":[175],"machine":[176],"learning":[177],"architectures":[178],"restricted":[180],"sampling":[181],"conditions.":[182],"This":[183],"establishes":[185],"robust,":[187],"flow-independent":[188],"foundation":[189],"dynamic":[192],"phenotyping.":[193]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-24T00:00:00"}