Cell phone based colorimetric analysis for point-of-care settings
Cell phones show considerable promise for point-of-care (POC) diagnostic procedures because they are accessible, connected, and computationally powerful. Cell phone image processing methods are being developed for the detection and quantification of a wide range of targets, employing methods from mi...
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| Published in: | Analyst (London) Vol. 144; no. 6; p. 1935 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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England
21.03.2019
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| ISSN: | 1364-5528, 1364-5528 |
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| Abstract | Cell phones show considerable promise for point-of-care (POC) diagnostic procedures because they are accessible, connected, and computationally powerful. Cell phone image processing methods are being developed for the detection and quantification of a wide range of targets, employing methods from microscopy to fluorescence techniques. However, most of the lab-based biological and biochemical assays still lack a robust and repeatable cell phone analogue. Existing solutions require external smartphone hardware to obtain quantitative results, imposing a design tradeoff between accessibility and accuracy. Here, we develop a cell phone imaging algorithm that enables analysis of assays that would typically be evaluated via spectroscopy. The developed technique uses the saturation parameter of hue-saturation-value color space to enable POC diagnosis. Through the analysis of over 10 000 images, we show that the saturation method consistently outperforms existing algorithms under a wide range of operating field conditions. The performance improvement is also proven analytically via the mathematic relationship between the saturation method and existing techniques. The method presented here is a step forward towards the development of POC diagnostics by reducing the required equipment, improving the limit of detection (LOD), and increasing the precision of quantitative results. |
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| AbstractList | Cell phones show considerable promise for point-of-care (POC) diagnostic procedures because they are accessible, connected, and computationally powerful. Cell phone image processing methods are being developed for the detection and quantification of a wide range of targets, employing methods from microscopy to fluorescence techniques. However, most of the lab-based biological and biochemical assays still lack a robust and repeatable cell phone analogue. Existing solutions require external smartphone hardware to obtain quantitative results, imposing a design tradeoff between accessibility and accuracy. Here, we develop a cell phone imaging algorithm that enables analysis of assays that would typically be evaluated via spectroscopy. The developed technique uses the saturation parameter of hue-saturation-value color space to enable POC diagnosis. Through the analysis of over 10 000 images, we show that the saturation method consistently outperforms existing algorithms under a wide range of operating field conditions. The performance improvement is also proven analytically via the mathematic relationship between the saturation method and existing techniques. The method presented here is a step forward towards the development of POC diagnostics by reducing the required equipment, improving the limit of detection (LOD), and increasing the precision of quantitative results. Cell phones show considerable promise for point-of-care (POC) diagnostic procedures because they are accessible, connected, and computationally powerful. Cell phone image processing methods are being developed for the detection and quantification of a wide range of targets, employing methods from microscopy to fluorescence techniques. However, most of the lab-based biological and biochemical assays still lack a robust and repeatable cell phone analogue. Existing solutions require external smartphone hardware to obtain quantitative results, imposing a design tradeoff between accessibility and accuracy. Here, we develop a cell phone imaging algorithm that enables analysis of assays that would typically be evaluated via spectroscopy. The developed technique uses the saturation parameter of hue-saturation-value color space to enable POC diagnosis. Through the analysis of over 10 000 images, we show that the saturation method consistently outperforms existing algorithms under a wide range of operating field conditions. The performance improvement is also proven analytically via the mathematic relationship between the saturation method and existing techniques. The method presented here is a step forward towards the development of POC diagnostics by reducing the required equipment, improving the limit of detection (LOD), and increasing the precision of quantitative results.Cell phones show considerable promise for point-of-care (POC) diagnostic procedures because they are accessible, connected, and computationally powerful. Cell phone image processing methods are being developed for the detection and quantification of a wide range of targets, employing methods from microscopy to fluorescence techniques. However, most of the lab-based biological and biochemical assays still lack a robust and repeatable cell phone analogue. Existing solutions require external smartphone hardware to obtain quantitative results, imposing a design tradeoff between accessibility and accuracy. Here, we develop a cell phone imaging algorithm that enables analysis of assays that would typically be evaluated via spectroscopy. The developed technique uses the saturation parameter of hue-saturation-value color space to enable POC diagnosis. Through the analysis of over 10 000 images, we show that the saturation method consistently outperforms existing algorithms under a wide range of operating field conditions. The performance improvement is also proven analytically via the mathematic relationship between the saturation method and existing techniques. The method presented here is a step forward towards the development of POC diagnostics by reducing the required equipment, improving the limit of detection (LOD), and increasing the precision of quantitative results. |
| Author | Coleman, Benjamin Asghar, Waseem Coarsey, Chad |
| Author_xml | – sequence: 1 givenname: Benjamin surname: Coleman fullname: Coleman, Benjamin email: wasghar@fau.edu organization: Asghar-Lab, Micro and Nanotechnology in Medicine, College of Engineering and Computer Science, Boca Raton, FL 33431, USA. wasghar@fau.edu – sequence: 2 givenname: Chad surname: Coarsey fullname: Coarsey, Chad organization: Department of Computer & Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA – sequence: 3 givenname: Waseem orcidid: 0000-0003-0458-8430 surname: Asghar fullname: Asghar, Waseem email: wasghar@fau.edu organization: Asghar-Lab, Micro and Nanotechnology in Medicine, College of Engineering and Computer Science, Boca Raton, FL 33431, USA. wasghar@fau.edu and Department of Computer & Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA and Department of Biological Sciences, Florida Atlantic University, Boca Raton, FL 33431, USA |
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| Snippet | Cell phones show considerable promise for point-of-care (POC) diagnostic procedures because they are accessible, connected, and computationally powerful. Cell... |
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| SubjectTerms | Algorithms Cell Phone Colorimetry - methods HIV - immunology HIV Core Protein p24 - immunology HIV Infections - diagnosis HIV Infections - immunology HIV Infections - virology Humans Image Processing, Computer-Assisted - instrumentation Limit of Detection Optical Imaging - methods Point-of-Care Systems |
| Title | Cell phone based colorimetric analysis for point-of-care settings |
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