{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T05:51:01Z","timestamp":1791179461595,"version":"4.1.0"},"reference-count":32,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T00:00:00Z","timestamp":1786492800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T00:00:00Z","timestamp":1786492800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100002803","name":"Fondazione Cariplo","doi-asserted-by":"publisher","award":["2021\u20101518"],"award-info":[{"award-number":["2021\u20101518"]}],"id":[{"id":"10.13039\/501100002803","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["analyticalsciencejournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Microscopy Res &amp;amp; Technique"],"published-print":{"date-parts":[[2026,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    With the increasing adoption of 3D cell cultures and bioprinting in biomedical research, there is a growing demand for reliable and accurate monitoring methods. While fluorescence microscopy is widely accepted for 2D cell cultures, when introducing the third dimension it often suffers from signal attenuation and out\u2010of\u2010focus interference, making automated image analysis challenging. In this study, a hybrid pipeline that integrates deep learning and traditional image processing techniques is presented with the aim of establishing an automated tool for cell segmentation and viability assessment in 3D from fluorescence microscopy images. A\n                    <jats:italic>U<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    \u2010Net architecture was trained on 2D cell cultures for cell segmentation, while watershed\u2010based separation and intensity\u2010based classification were employed for viability detection. The model demonstrated accurate segmentation with minimal overfitting. Quantitative comparisons with manual counts and ImageJ\u2010based results confirmed its accuracy. We then demonstrated the possibility of extending this model to 3D constructs by tracking cell density and viability during time in the case of human umbilical vein endothelial cells bioprinted in gelatin methacrylate at different seeding densities, taken as case study. Automated counts closely matched manual ones, highlighting the method reliability and minimal invasiveness avoiding the need for sacrificing the construct. Hence, this approach provides a scalable, reproducible, and efficient alternative to manual counting in 3D environments, enabling high\u2010throughput analysis of complex fluorescence microscopy data.\n                  <\/jats:p>","DOI":"10.1002\/jemt.70170","type":"journal-article","created":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T07:52:30Z","timestamp":1786521150000},"page":"1327-1338","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Deep Learning Pipeline for Cell Segmentation and Viability Quantification in\n                    <scp>3D<\/scp>\n                    Constructs From Fluorescence Microscopy Images"],"prefix":"10.1002","volume":"89","author":[{"given":"Federica","family":"Valtellina","sequence":"first","affiliation":[{"name":"Department of Chemistry Materials and Chemical Engineering \u201cGiulio Natta,\u201d Politecnico di Milano  Milano Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6110-4260","authenticated-orcid":false,"given":"Francesco","family":"Iannacci","sequence":"additional","affiliation":[{"name":"Department of Chemistry Materials and Chemical Engineering \u201cGiulio Natta,\u201d Politecnico di Milano  Milano Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6844-2030","authenticated-orcid":false,"given":"Bianca Maria","family":"Colosimo","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering Politecnico di Milano  Milano Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8130-6495","authenticated-orcid":false,"given":"Mattia","family":"Sponchioni","sequence":"additional","affiliation":[{"name":"Department of Chemistry Materials and Chemical Engineering \u201cGiulio Natta,\u201d Politecnico di Milano  Milano Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,12]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"crossref","unstructured":"Alahmari S. D.Goldgof L.Hall andP.Mouton.2019.\u201cAutomatic Cell Counting Using Active Deep Learning and Unbiased Stereology.\u201dPaper presented at 2019 IEEE International Conference on Systems Man and Cybernetics (SMC) Bari Italy October 6\u20139.","DOI":"10.1109\/SMC.2019.8914199"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1049\/htl.2018.5098"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-30695-9"},{"issue":"12","key":"e_1_2_10_5_1","article-title":"Medical Image Segmentation Review: The Success of U\u2010Net","volume":"46","author":"Azad R.","year":"2024","journal-title":"IEE Explore"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1039\/D2SM00018K"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.drudis.2012.10.003"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/ima.23052"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1089\/ten.tec.2012.0486"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/mame.201200122"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.128630"},{"key":"e_1_2_10_12_1","doi-asserted-by":"crossref","unstructured":"He S. K.Minn L.Solnica\u2010Krezel M.Anastasio andH.Li.2019.\u201cAutomatic Microscopic Cell Counting by Use of Deeply\u2010Supervised Density Regression Model.\u201dComputer Vision and Pattern Recognition. 10956 109560L.","DOI":"10.1117\/12.2513045"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/smll.201805510"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.displa.2025.102968"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.3390\/app11114912"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11517-024-03205-w"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1088\/1758-5090\/adb891"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.biomaterials.2019.119536"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-019-0403-1"},{"key":"e_1_2_10_20_1","article-title":"Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins","volume":"11","author":"O'Brien J.","year":"2016","journal-title":"Journal of Visualized Experiments"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tibtech.2015.04.005"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.drudis.2016.04.006"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2014.09.004"},{"key":"e_1_2_10_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107404"},{"key":"e_1_2_10_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainres.2019.146393"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1002\/ima.23203"},{"key":"e_1_2_10_27_1","doi-asserted-by":"publisher","DOI":"10.1039\/D2BM02060B"},{"key":"e_1_2_10_28_1","doi-asserted-by":"publisher","DOI":"10.1002\/jemt.20859"},{"key":"e_1_2_10_29_1","doi-asserted-by":"publisher","DOI":"10.1142\/S1793545825300113"},{"key":"e_1_2_10_30_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2019.04.006"},{"key":"e_1_2_10_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13244-018-0639-9"},{"key":"e_1_2_10_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.isci.2024.109740"},{"key":"e_1_2_10_33_1","doi-asserted-by":"publisher","DOI":"10.3390\/info15040198"}],"container-title":["Microscopy Research and Technique"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/analyticalsciencejournals.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jemt.70170","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/analyticalsciencejournals.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/jemt.70170","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/analyticalsciencejournals.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/jemt.70170","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T04:51:13Z","timestamp":1791175873000},"score":1,"resource":{"primary":{"URL":"https:\/\/analyticalsciencejournals.onlinelibrary.wiley.com\/doi\/10.1002\/jemt.70170"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,12]]},"references-count":32,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2026,11]]}},"alternative-id":["10.1002\/jemt.70170"],"URL":"https:\/\/doi.org\/10.1002\/jemt.70170","archive":["Portico"],"relation":{},"ISSN":["1059-910X","1097-0029"],"issn-type":[{"value":"1059-910X","type":"print"},{"value":"1097-0029","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,12]]},"assertion":[{"value":"2026-02-14","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-08-04","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-08-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}