A smart phone-based robust correction algorithm for the colorimetric detection of Urinary Tract Infection

Area of Science:

• Biomedical Engineering
• Medical Diagnostics
• Mobile Health (mHealth)

Background:

• Urinary Tract Infections (UTIs) are common, requiring accessible diagnostic methods.
• Current point-of-care diagnostics often rely on specialized equipment.
• Smartphone technology offers potential for portable medical devices.

Purpose of the Study:

• To develop a smartphone application for colorimetric detection of UTIs.
• To enable nurses and medical personnel to perform diagnostics without strip readers.
• To address the challenge of consistent camera color perception across varying conditions.

Main Methods:

• Utilized a smartphone-based application for colorimetric analysis.
• Implemented a black and white reference correction method.
• Applied comprehensive color image normalization techniques.

Main Results:

• Preliminary work demonstrates the feasibility of smartphone-based UTI detection.
• Comprehensive color image normalization effectively corrected for illumination differences.
• The developed methods show promise for a practical, equipment-free diagnostic solution.

Conclusions:

• Smartphone colorimetric analysis is a viable approach for UTI detection.
• Color image normalization is crucial for reliable results in diverse lighting.
• Further development can lead to a practical point-of-care diagnostic tool.