{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T14:43:58Z","timestamp":1792593838563,"version":"4.5.0"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["R37-CA214955"],"award-info":[{"award-number":["R37-CA214955"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,20]]},"abstract":"<jats:title>SUMMARY<\/jats:title>\n                  <jats:p>Recent advances in multiplex imaging have enabled researchers to locate different types of cells within a tissue sample. This is especially relevant for tumor immunology, as clinical regimes corresponding to different stages of disease or responses to treatment may manifest as different spatial arrangements of tumor and immune cells. Spatial point pattern modeling can be used to partition multiplex tissue images according to these regimes. To this end, we propose a two-stage approach: first, local intensities and pair correlation functions are estimated from the spatial point pattern of cells within each image, and the pair correlation functions are reduced in dimension via spectral decomposition of the covariance function. Second, the estimates are clustered in a Bayesian hierarchical model with spatially-dependent cluster labels. The clusters correspond to regimes of interest that are present across subjects; the cluster labels segment the spatial point patterns according to those regimes. Through Markov Chain Monte Carlo sampling, we jointly estimate and quantify uncertainty in the cluster assignment and spatial characteristics of each cluster. Simulations demonstrate the performance of the method, and it is applied to a set of multiplex immunofluorescence images of diseased pancreatic tissue.<\/jats:p>","DOI":"10.1093\/biostatistics\/kxaf049","type":"journal-article","created":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T13:02:30Z","timestamp":1764162150000},"source":"Crossref","is-referenced-by-count":0,"title":["A two-stage approach for segmenting spatial point patterns applied to multiplex imaging"],"prefix":"10.1093","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1396-256X","authenticated-orcid":false,"given":"Alvin","family":"Sheng","sequence":"first","affiliation":[{"name":"University of Minnesota Division of Biostatistics and Health Data Science, , 2221 University Avenue SE , Minneapolis, MN 55414,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brian J","family":"Reich","sequence":"additional","affiliation":[{"name":"North Carolina State University Department of Statistics, , 2311 Stinson Drive , Raleigh, NC 27605,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7434-8726","authenticated-orcid":false,"given":"Ana-Maria","family":"Staicu","sequence":"additional","affiliation":[{"name":"North Carolina State University Department of Statistics, , 2311 Stinson Drive , Raleigh, NC 27605,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Santhoshi N","family":"Krishnan","sequence":"additional","affiliation":[{"name":"University of Michigan Department of Computational Medicine and Bioinformatics, , 100 Washtenaw Avenue , Ann Arbor, MI 48109,","place":["United States"]},{"name":"Rice University Department of Electrical and Computer Engineering, , 6100 Main Street , Houston, TX 77005,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arvind","family":"Rao","sequence":"additional","affiliation":[{"name":"University of Michigan Department of Computational Medicine and Bioinformatics, , 100 Washtenaw Avenue , Ann Arbor, MI 48109,","place":["United States"]},{"name":"Rice University Department of Electrical and Computer Engineering, , 6100 Main Street , Houston, TX 77005,","place":["United States"]},{"name":"University of Michigan School of Public Health Department of Biostatistics, , 1415 Washington Heights , Ann Arbor, MI 48109,","place":["United States"]},{"name":"University of Michigan Medical School Department of Radiation Oncology, , 1500 E Medical Center Drive , Ann Arbor, MI 48109,","place":["United States"]},{"name":"University of Michigan Department of Biomedical Engineering, , 2200 Bonisteel Boulevard , Ann Arbor, MI 48109,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5987-0404","authenticated-orcid":false,"given":"Timothy L","family":"Frankel","sequence":"additional","affiliation":[{"name":"University of Michigan Medical School Department of Surgery, , 1500 E Medical Center Drive , Ann Arbor, MI 48109,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,1,20]]},"reference":[{"key":"2026102110232467800_kxaf049-B1","first-page":"1485\u2013","article-title":"Nonparametric maximum likelihood estimation of features in spatial point processes using Vorono\u00ef tessellation","volume":"92","author":"Allard","year":"1997","journal-title":"J Am Stat Assoc."},{"key":"2026102110232467800_kxaf049-B2","doi-asserted-by":"crossref","first-page":"R921\u2013","DOI":"10.1016\/j.cub.2020.06.081","article-title":"The tumor 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