{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T18:54:49Z","timestamp":1774292089434,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,1,13]],"date-time":"2021-01-13T00:00:00Z","timestamp":1610496000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61827806"],"award-info":[{"award-number":["61827806"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Qianjiang Talent Project Type-D of Zhejiang","award":["QJD1802021"],"award-info":[{"award-number":["QJD1802021"]}]},{"name":"Talent Cultivation Project of Zhejiang Association for Science and Technology","award":["CTZB-2020080127-19"],"award-info":[{"award-number":["CTZB-2020080127-19"]}]},{"DOI":"10.13039\/100022955","name":"Fundamental Research Funds for the Provincial Universities of Zhejiang","doi-asserted-by":"crossref","award":["GK209907299001-305"],"award-info":[{"award-number":["GK209907299001-305"]}],"id":[{"id":"10.13039\/100022955","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Sensors"],"abstract":"<jats:p>The differential count of white blood cells (WBCs) is one widely used approach to assess the status of a patient\u2019s immune system. Currently, the main methods of differential WBC counting are manual counting and automatic instrument analysis with labeling preprocessing. But these two methods are complicated to operate and may interfere with the physiological states of cells. Therefore, we propose a deep learning-based method to perform label-free classification of three types of WBCs based on their morphologies to judge the activated or inactivated neutrophils. Over 90% accuracy was finally achieved by a pre-trained fine-tuning Resnet-50 network. This deep learning-based method for label-free WBC classification can tackle the problem of complex instrumental operation and interference of fluorescent labeling to the physiological states of the cells, which is promising for future point-of-care applications.<\/jats:p>","DOI":"10.3390\/s21020512","type":"journal-article","created":{"date-parts":[[2021,1,13]],"date-time":"2021-01-13T21:50:54Z","timestamp":1610574654000},"page":"512","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Deep-Learning Based Label-Free Classification of Activated and Inactivated Neutrophils for Rapid Immune State Monitoring"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2364-0479","authenticated-orcid":false,"given":"Xiwei","family":"Huang","sequence":"first","affiliation":[{"name":"Key Laboratory of RF Circuits and Systems, Ministry of Education, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyungkook","family":"Jeon","sequence":"additional","affiliation":[{"name":"Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jixuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of RF Circuits and Systems, Ministry of Education, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangfan","family":"Yao","sequence":"additional","affiliation":[{"name":"Key Laboratory of RF Circuits and Systems, Ministry of Education, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maoyu","family":"Wei","sequence":"additional","affiliation":[{"name":"Key Laboratory of RF Circuits and Systems, Ministry of Education, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wentao","family":"Han","sequence":"additional","affiliation":[{"name":"Key Laboratory of RF Circuits and Systems, Ministry of Education, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of RF Circuits and Systems, Ministry of Education, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingling","family":"Sun","sequence":"additional","affiliation":[{"name":"Key Laboratory of RF Circuits and Systems, Ministry of Education, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jongyoon","family":"Han","sequence":"additional","affiliation":[{"name":"Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"},{"name":"Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"},{"name":"Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"721","DOI":"10.1016\/j.jpeds.2006.08.051","article-title":"Comparison of total white blood cell count and serum C-reactive protein levels in confirmed bacterial and viral infections","volume":"149","author":"Peltola","year":"2006","journal-title":"J. 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