An Efficient System for Automatic Blood Type Determination Based on Image Matching Techniques

Nuha Odeh,Yousef Dama,Farah Oshaibi,Muna Shaar,Falah Mohammed,Anas Toma

doi:10.3390/app11115225

Nuha Odeh, Yousef Dama + Show 4 more

Open Access

https://doi.org/10.3390/app11115225

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Journal: Applied Sciences	Publication Date: Jun 4, 2021
Citations: 6	License type: CC BY 4.0

Affiliation: An-Najah National University

Abstract

This paper presents a fast and accurate system to determine the type of blood automatically based on image processing. Blood type determination is important in emergency situations, where there is a need for blood transfusion to save lives. The traditional blood determination techniques are performed manually by a specialist in medical labs, where the result requires a long time or may be affected by human error. This may cause serious consequences or even endanger people’s lives. The proposed approach performs blood determination in real-time with low cost using any available mobile device equipped with a camera. A total of 500 blood samples were processed in this study using different image matching techniques including oriented fast and rotated brief (ORB), scale invariant feature transform (SIFT), and speed-up robust feature (SURF). The evaluation results show that our proposed system, which adopts the ORB algorithm, is the fastest and the most accurate among the state-of-the-art systems. It can achieve an accuracy of 99.6% in an average time of 250 ms.

Highlights

Determining a patient’s blood type is one of the most important and essential steps to be performed before treating injured people
To detect the agglutination formed in a given blood sample using the scale invariant feature transform (SIFT) algorithm, a comparison between the reference blood image shown in Figure 13 and the input blood sample is made
When the SIFT algorithm is applied to the blood spot mixed with anti-A, it can be noticed that the SIFT algorithm is sensitive to variations in brightness

Summary

Introduction

Determining a patient’s blood type (blood typing) is one of the most important and essential steps to be performed before treating injured people Such a step should be accomplished with precision and accuracy in a timely manner to save lives and avoid serious consequences, especially in emergency situations. These traditional methods are performed manually by lab technicians and are subjected to human error and delays. Image analysis techniques have been adopted in automatic blood typing to provide fast and objective decisions [4,5,6,7,8,9]

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