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Image enhancement variational methods for Enabling Strong Cost Reduction in OLED-based Point-of-Care Immunofluorescent Diagnostic Systems

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Bibliographic Details
Title: Image enhancement variational methods for Enabling Strong Cost Reduction in OLED-based Point-of-Care Immunofluorescent Diagnostic Systems
Authors: Damiana Lazzaro, Serena Morigi, P. Melpignano, E. Loli Piccolomini, Luca Benini
Contributors: Damiana, Lazzaro, Serena, Morigi, Melpignano, P., Loli Piccolomini, E., Luca, Benini
Publication Year: 2018
Collection: IRIS Università degli Studi di Bologna (CRIS - Current Research Information System)
Subject Terms: Variational image processing, image segmentation, image super-resolution, immunofluorescience technique, CMOS image sensors
Description: Objective:Immunofluorescence diagnostic systems cost is often dominated by high-sensitivity, low-noise CCD-based cameras which are used to acquire the fluorescence images. In this paper we investigate the use of low-cost CMOS sensors in a point-of-care immunofluorescence diagnostic application for the detection and discrimination of four different serotypes of the Dengue virus in a set of human samples. Methods: A two-phase post-processing software pipeline is proposed which consists in a first image enhancement stage for resolution increasing and segmentation, and a second diagnosis stage for the computation of the output concentrations. Results: We present a novel variational coupled model for the joint super-resolution and segmentation stage, and an automatic innovative image analysis for the diagnosis purpose. A specially designed Forward Backward-based numerical algorithm is introduced and its convergence is proved under mild conditions. We present results on a cheap prototype CMOS camera compared with the results of a more expensive CCD device, for the detection of the Dengue virus with a low-cost OLED light source. The combinationoftheCMOSsensorandthedevelopedpost-processingsoftwareallowstocorrectlyidentifythe different Dengue serotype using an automatized procedure. Conclusions: The results demonstrate that our diagnostic imaging system enables camera cost reduction up to 99%, at an acceptable diagnostic accuracy, with respect to the reference CCD-based camera system. The correct detection and identification of the Dengue serotypes has been confirmed by standard diagnostic methods (RT-PCR and ELISA)
Document Type: article in journal/newspaper
File Description: STAMPA
Language: English
Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:000426612100006; volume:34; issue:3; firstpage:2932; lastpage:2951; numberofpages:20; journal:INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING; info:eu-repo/grantAgreement/EC/FP7/291125; http://hdl.handle.net/11585/614467
DOI: 10.1002/cnm.2932
Availability: http://hdl.handle.net/11585/614467
https://doi.org/10.1002/cnm.2932
https://onlinelibrary.wiley.com/doi/10.1002/cnm.2932
Rights: info:eu-repo/semantics/openAccess
Accession Number: edsbas.166B6BAF
Database: BASE
Description
Abstract:Objective:Immunofluorescence diagnostic systems cost is often dominated by high-sensitivity, low-noise CCD-based cameras which are used to acquire the fluorescence images. In this paper we investigate the use of low-cost CMOS sensors in a point-of-care immunofluorescence diagnostic application for the detection and discrimination of four different serotypes of the Dengue virus in a set of human samples. Methods: A two-phase post-processing software pipeline is proposed which consists in a first image enhancement stage for resolution increasing and segmentation, and a second diagnosis stage for the computation of the output concentrations. Results: We present a novel variational coupled model for the joint super-resolution and segmentation stage, and an automatic innovative image analysis for the diagnosis purpose. A specially designed Forward Backward-based numerical algorithm is introduced and its convergence is proved under mild conditions. We present results on a cheap prototype CMOS camera compared with the results of a more expensive CCD device, for the detection of the Dengue virus with a low-cost OLED light source. The combinationoftheCMOSsensorandthedevelopedpost-processingsoftwareallowstocorrectlyidentifythe different Dengue serotype using an automatized procedure. Conclusions: The results demonstrate that our diagnostic imaging system enables camera cost reduction up to 99%, at an acceptable diagnostic accuracy, with respect to the reference CCD-based camera system. The correct detection and identification of the Dengue serotypes has been confirmed by standard diagnostic methods (RT-PCR and ELISA)
DOI:10.1002/cnm.2932