Phase-Driven Classification for Improved Detection of Malaria-Infected Red Blood Cells in Digital Holographic Microscopy

Phase-Driven Classification for Improved Detection of Malaria-Infected Red Blood Cells in Digital Holographic Microscopy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Phase-Driven Classification for Improved Detection of Malaria-Infected Red Blood Cells in Digital Holographic Microscopy Charlotte Kyeremah, Aditya S. Paul, Daniel Haehn, Manoj T. Duraisingh, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6246651/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Aug, 2025 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Digital holographic microscopy (DHM) has emerged as a powerful, label-free technique for visualizing and analyzing biological samples. By extracting the intrinsic optical properties of red blood cells (RBCs), DHM enables the detection of infection-induced morphological and biophysical changes. Traditional classification methods often rely on feature-specific analysis, which can lead to misclassification when a single parameter fails to differentiate between uninfected and infected cells. In this study, we present a novel features-based approach that integrates multiple characteristics to classify Plasmodium falciparum -infected RBCs obtained using lensless inline DHM. Our analysis shows that phase-based features provide a more reliable indicator of infected RBCs compared to morphological features. Additionally, our features-based approach, which considers multiple characteristics collectively, outperforms feature-specific methods that rely on individual attributes. The parasitemia detection rate improved from 48% (feature-specific method) to 61% (phase-based features method) on the same sample set, demonstrating enhanced detection accuracy. Furthermore, the proposed method achieved high specificity (98–100%), ensuring reliable identification of uninfected cells. Although our method slightly underestimates the parasitemia detection rate compared to Giemsa staining (90%), it offers a significant advantage as a real-time, label-free imaging tool, presenting a promising avenue for rapid and automated malaria diagnosis. Physical sciences/Optics and photonics/Optical techniques/Microscopy Physical sciences/Optics and photonics/Optical techniques/Microscopy/Interference microscopy Physical sciences/Optics and photonics/Optical techniques/Microscopy/Phase contrast microscopy Physical sciences/Optics and photonics/Optical techniques/Imaging and sensing Lensless inline digital holographic microscopy malaria diagnosis red blood cell classification Features-based classification morphology analysis phase-based thresholding Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 21 Aug, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 28 May, 2025 Reviews received at journal 27 May, 2025 Reviewers agreed at journal 01 May, 2025 Reviews received at journal 25 Apr, 2025 Reviews received at journal 20 Apr, 2025 Reviewers agreed at journal 30 Mar, 2025 Reviewers agreed at journal 30 Mar, 2025 Reviewers invited by journal 29 Mar, 2025 Editor assigned by journal 28 Mar, 2025 Editor invited by journal 28 Mar, 2025 Submission checks completed at journal 27 Mar, 2025 First submitted to journal 17 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6246651","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":436192151,"identity":"7aa38998-2244-4ab6-8243-a1e60c75ce51","order_by":0,"name":"Charlotte Kyeremah","email":"","orcid":"","institution":"University of Massachusetts Boston","correspondingAuthor":false,"prefix":"","firstName":"Charlotte","middleName":"","lastName":"Kyeremah","suffix":""},{"id":436192152,"identity":"5361090c-caec-4ccc-bc33-f896e3626906","order_by":1,"name":"Aditya S. Paul","email":"","orcid":"","institution":"Harvard T.H. 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