On the characterization of bias errors in defocusing-based 3D particle tracking velocimetry for microfluidics

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This study theoretically and experimentally characterizes bias errors in defocusing particle tracking velocimetry for microfluidics, identifying field curvature and refractive index mismatch as main sources and proposing a correction methodology.

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The paper studies bias errors in defocusing-based 3D particle tracking velocimetry (DPT) for microfluidic applications, combining systematic theoretical analysis with experiments across multiple microscope and microfluidic setups. It identifies field curvature aberration and refractive index mismatch as the main sources of bias and proposes a correction methodology that determines the curved focal plane using a reference Poiseuille flow measurement, with special treatment for refractive index mismatch. The authors validate the approach and quantify bias errors on 10 experimental setups spanning different working fluids, materials, geometries, and objective magnifications from 5× to 40×, concluding that the magnitude of such biases is generally not predictable and should be evaluated case by case. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

In this work, we provide a systematic theoretical and experimental characterization of bias errors in defocusing particle tracking (DPT) methods with respect to microfluidic applications. Bias errors are often neglected in DPT measurements and to date only few works reported empirical procedures to compensate for that. A generalized bias correction procedure as well as a systematic characterization of the impact of such error in DPT measurements is still lacking.We show that the field curvature aberration and the refractive index mismatch are the main sources of bias error in these applications. We propose a correction methodology based on the determination of the curved focal plane by means of a reference measurement of a Poiseuille flow.We discuss the impact of the refractive index mismatch and how to correctly compensate for it. We validated our methodology and quantified the bias errors on 10 different experimental setups, using different working fluids, materials, geometries, and microscope objective lenses ranging from 5 \(\times\) to 40$\times$ magnification. Our results indicate that the impact of this type of bias errors is in general not predictable and must be evaluated case by case. The proposed methodology allows to estimate and minimize the bias error in most microfluidic setups and is suitable for any single-camera DPT approach.
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On the characterization of bias errors in defocusing-based 3D particle tracking velocimetry for microfluidics | 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 Research Article On the characterization of bias errors in defocusing-based 3D particle tracking velocimetry for microfluidics Gonçalo Coutinho, Ana Moita, Ana Ribeiro, António Moreira, Massimiliano Rossi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2168914/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 May, 2023 Read the published version in Experiments in Fluids → Version 1 posted 7 You are reading this latest preprint version Abstract In this work, we provide a systematic theoretical and experimental characterization of bias errors in defocusing particle tracking (DPT) methods with respect to microfluidic applications. Bias errors are often neglected in DPT measurements and to date only few works reported empirical procedures to compensate for that. A generalized bias correction procedure as well as a systematic characterization of the impact of such error in DPT measurements is still lacking.We show that the field curvature aberration and the refractive index mismatch are the main sources of bias error in these applications. We propose a correction methodology based on the determination of the curved focal plane by means of a reference measurement of a Poiseuille flow.We discuss the impact of the refractive index mismatch and how to correctly compensate for it. We validated our methodology and quantified the bias errors on 10 different experimental setups, using different working fluids, materials, geometries, and microscope objective lenses ranging from 5 \(\times\) to 40 $ \times $ magnification. Our results indicate that the impact of this type of bias errors is in general not predictable and must be evaluated case by case. The proposed methodology allows to estimate and minimize the bias error in most microfluidic setups and is suitable for any single-camera DPT approach. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 19 May, 2023 Read the published version in Experiments in Fluids → Version 1 posted Editorial decision: Major revision 14 Jan, 2023 Reviews received at journal 16 Dec, 2022 Reviewers agreed at journal 14 Nov, 2022 Reviewers invited by journal 12 Nov, 2022 Editor assigned by journal 18 Oct, 2022 Submission checks completed at journal 18 Oct, 2022 First submitted to journal 15 Oct, 2022 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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