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Proceedings Paper

Measurement of glucose concentration by image processing of thin film slides
Author(s): Sankaranaryanan Piramanayagam; Eli Saber; David Heavner
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Paper Abstract

Measurement of glucose concentration is important for diagnosis and treatment of diabetes mellitus and other medical conditions. This paper describes a novel image-processing based approach for measuring glucose concentration. A fluid drop (patient sample) is placed on a thin film slide. Glucose, present in the sample, reacts with reagents on the slide to produce a color dye. The color intensity of the dye formed varies with glucose at different concentration levels. Current methods use spectrophotometry to determine the glucose level of the sample. Our proposed algorithm uses an image of the slide, captured at a specific wavelength, to automatically determine glucose concentration. The algorithm consists of two phases: training and testing. Training datasets consist of images at different concentration levels. The dye-occupied image region is first segmented using a Hough based technique and then an intensity based feature is calculated from the segmented region. Subsequently, a mathematical model that describes a relationship between the generated feature values and the given concentrations is obtained. During testing, the dye region of a test slide image is segmented followed by feature extraction. These two initial steps are similar to those done in training. However, in the final step, the algorithm uses the model (feature vs. concentration) obtained from the training and feature generated from test image to predict the unknown concentration. The performance of the image-based analysis was compared with that of a standard glucose analyzer.

Paper Details

Date Published: 24 February 2012
PDF: 7 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83144U (24 February 2012); doi: 10.1117/12.910978
Show Author Affiliations
Sankaranaryanan Piramanayagam, Rochester Institute of Technology (United States)
Eli Saber, Rochester Institute of Technology (United States)
David Heavner, Ortho Clinical Diagnostics, Inc. (United States)


Published in SPIE Proceedings Vol. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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