{"id":"https://openalex.org/W7134821580","doi":"https://doi.org/10.48550/arxiv.2603.06936","title":"Extracting and analyzing 3D histomorphometric features related to perineural and lymphovascular invasion in prostate cancer","display_name":"Extracting and analyzing 3D histomorphometric features related to perineural and lymphovascular invasion in prostate cancer","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7134821580","doi":"https://doi.org/10.48550/arxiv.2603.06936"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.06936","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","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/A5003993513","display_name":"Sarah S. L. Chow","orcid":"https://orcid.org/0009-0005-7519-9346"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chow, Sarah S. L.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128663184","display_name":"rui wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Rui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046956648","display_name":"Robert Serafin","orcid":"https://orcid.org/0000-0002-6646-353X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Serafin, Robert B.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128666160","display_name":"Yujie Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Yujie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092788666","display_name":"Elena Baraznenok","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baraznenok, Elena","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121680927","display_name":"Xavier Farr\u00e9","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Farr\u00e9, Xavier","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116734173","display_name":"Jennifer Salguero-Lopez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Salguero-Lopez, Jennifer","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128665903","display_name":"Gan Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Gan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078116468","display_name":"Huai-Ching Hsieh","orcid":"https://orcid.org/0000-0003-4722-1444"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hsieh, Huai-Ching","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128647768","display_name":"Lawrence D. True","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"True, Lawrence D.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128674744","display_name":"Priti Lal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lal, Priti","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128688869","display_name":"Anant Madabhushi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Madabhushi, Anant","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100627890","display_name":"Jonathan Liu","orcid":"https://orcid.org/0000-0001-5650-3086"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jonathan T. C.","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28883927,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T10862","display_name":"AI in cancer detection","score":0.3962000012397766,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10862","display_name":"AI in cancer detection","score":0.3962000012397766,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10124","display_name":"Prostate Cancer Diagnosis and Treatment","score":0.17839999496936798,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.08590000122785568,"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/prostate-cancer","display_name":"Prostate cancer","score":0.777400016784668},{"id":"https://openalex.org/keywords/perineural-invasion","display_name":"Perineural invasion","score":0.7508999705314636},{"id":"https://openalex.org/keywords/prostatectomy","display_name":"Prostatectomy","score":0.6945000290870667},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6629999876022339},{"id":"https://openalex.org/keywords/lymphovascular-invasion","display_name":"Lymphovascular invasion","score":0.5679000020027161},{"id":"https://openalex.org/keywords/grading","display_name":"Grading (engineering)","score":0.5422999858856201},{"id":"https://openalex.org/keywords/digital-pathology","display_name":"Digital pathology","score":0.459199994802475}],"concepts":[{"id":"https://openalex.org/C2780192828","wikidata":"https://www.wikidata.org/wiki/Q181257","display_name":"Prostate cancer","level":3,"score":0.777400016784668},{"id":"https://openalex.org/C2777154038","wikidata":"https://www.wikidata.org/wiki/Q7168585","display_name":"Perineural invasion","level":3,"score":0.7508999705314636},{"id":"https://openalex.org/C2779466945","wikidata":"https://www.wikidata.org/wiki/Q1765251","display_name":"Prostatectomy","level":4,"score":0.6945000290870667},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6629999876022339},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.5716999769210815},{"id":"https://openalex.org/C2778740770","wikidata":"https://www.wikidata.org/wiki/Q6708283","display_name":"Lymphovascular invasion","level":4,"score":0.5679000020027161},{"id":"https://openalex.org/C2777286243","wikidata":"https://www.wikidata.org/wiki/Q5591926","display_name":"Grading (engineering)","level":2,"score":0.5422999858856201},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.531000018119812},{"id":"https://openalex.org/C2777522853","wikidata":"https://www.wikidata.org/wiki/Q5276128","display_name":"Digital pathology","level":2,"score":0.459199994802475},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41519999504089355},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.41350001096725464},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4049000144004822},{"id":"https://openalex.org/C2776235491","wikidata":"https://www.wikidata.org/wiki/Q9625","display_name":"Prostate","level":3,"score":0.399399995803833},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.3310999870300293},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3158999979496002},{"id":"https://openalex.org/C57742111","wikidata":"https://www.wikidata.org/wiki/Q7168","display_name":"Histology","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.25279998779296875}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.06936","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.06936","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.06936","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":"Preprint"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.06936","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.40432536602020264}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Diagnostic":[0],"grading":[1],"of":[2,10,18,44,90,107,120,155,162,166],"prostate":[3],"cancer":[4],"(PCa)":[5],"relies":[6],"on":[7,61,144],"the":[8,15,145,163],"examination":[9],"2D":[11,22,28,56,193],"histology":[12],"sections.":[13],"However,":[14],"limited":[16],"sampling":[17],"specimens":[19,110],"afforded":[20],"by":[21,64],"histopathology,":[23],"and":[24,46,78,102,122,130,137,191],"ambiguities":[25],"when":[26],"viewing":[27],"cross-sections,":[29],"can":[30,48],"lead":[31],"to":[32,54,69,74,99,176],"suboptimal":[33],"treatment":[34],"decisions.":[35],"Recent":[36],"studies":[37],"have":[38],"shown":[39],"that":[40,111,184],"3D":[41,71,93,105,146,153,185],"histomorphometric":[42],"analysis":[43],"glands":[45],"nuclei":[47],"improve":[49],"PCa":[50],"risk":[51],"assessment":[52],"compared":[53],"analogous":[55],"features.":[57],"Here,":[58],"we":[59,169],"expand":[60],"these":[62,167],"efforts":[63],"developing":[65],"an":[66],"analytical":[67],"pipeline":[68],"extract":[70],"features":[72,187,195],"related":[73],"perineural":[75],"invasion":[76,80],"(PNI)":[77],"lymphovascular":[79],"(LVI),":[81],"which":[82],"correlate":[83],"with":[84,116,124,152],"poor":[85],"prognosis":[86],"for":[87],"a":[88,117,159,171],"variety":[89],"cancers.":[91],"A":[92],"segmentation":[94,148],"model":[95],"(nnU-Net)":[96],"was":[97],"trained":[98,170],"segment":[100],"nerves":[101],"vessels":[103],"in":[104,150],"datasets":[106],"archived":[108],"prostatectomy":[109],"were":[112,140],"optically":[113],"cleared,":[114],"labeled":[115],"fluorescent":[118],"analog":[119],"H&E,":[121],"imaged":[123],"open-top":[125],"light-sheet":[126],"(OTLS)":[127],"microscopy.":[128],"PNI-":[129],"LVI-related":[131],"features,":[132,168],"including":[133],"metrics":[134],"describing":[135],"cancer-nerve":[136],"cancer-vessel":[138],"proximity,":[139],"then":[141],"extracted":[142],"based":[143],"nerve/vessel":[147],"masks":[149,154],"conjunction":[151],"cancer-enriched":[156],"regions.":[157],"As":[158],"preliminary":[160],"exploration":[161],"prognostic":[164,190],"value":[165],"supervised":[172],"machine":[173],"learning":[174],"classifier":[175],"predict":[177],"5-year":[178],"biochemical":[179],"recurrence":[180],"(BCR)":[181],"outcomes,":[182],"finding":[183],"PNI-related":[186,194],"are":[188],"moderately":[189],"outperform":[192],"(AUC":[196],"=":[197],"0.71":[198],"vs.":[199],"0.52).":[200],"Source":[201],"code":[202],"is":[203],"available":[204],"at":[205],"https://github.com/sarahrahsl/SegCIA.git.":[206]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-11T00:00:00"}