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Digitisation of blood type cards

Case

Digitisation of blood type cards

Mobile application exploits machine learning to automatically read blood type cards from Eldon Biologicals

Using computer vision techniques, we have, in collaboration with Eldon Biologicals, developed an algorithm that can read blood and translate it into numbers to determine an individual’s blood type.

How do you determine whether an individual has blood type A, B, AB or O? In Denmark, this is automatically determined in the blood banks, but in developing countries where advanced equipment for analysing a blood test is not available, the so-called EldonCards remain an important tool for physicians and health professionals.

The card, invented by the Danish physician Knud Eldon in 1954, is a piece of plastic with four circles of antibodies. If a drop of blood is transferred to each of the four circles, a grainy structure called agglutination may develop in each of the circles depending on the blood type. In case of non-agglutination, the blood in the circle remains a homogeneous red colour.

Therefore, Eldon Biologicals that sells the cards came up with the idea of developing an algorithm that can distinguish whether the blood clots, i.e. agglutinates, or remains a homogeneous red colour.

In collaboration with our Visual Computing Lab, they have developed a prototype of a mobile application that is able to read the blood type based on the blood deposited on the card. The application can then send the result to a blood bank or others who have an interest in the result. It can also tell if the blood type determination is not performed correctly and therefore faulty.

The application works by taking a picture of the blood type cards. On the circles of the card, an active substance is either activated so that the red blood cells accumulate and thus clot (agglutinate), or the blood remains a homogeneous red colour.

Visual Computing Lab has made various image operations on the cards that provide visual information about the texture of the blood. The information is combined into a descriptive code number that can be used to determine whether or not the blood in a circle is agglutinated. The algorithm is trained and validated on the basis of a lot of cards where we know what the result is.

Freely translated this means that based on training images a high-dimensional space has been defined that can be divided so that the agglutinated circles occupy part of the space and the non-agglutinated another part. This means that today we have a motor that works. It is a model that with a close to 100 percent says whether or not a result has been found.

Eldon Biological's customers include field hospitals and relief organisations operating primarily in third world countries. In the United States, the cards are used for blood type determination in private homes, e.g. if people want to eat according to their blood type.

The company is a co-founder of and collaborates with the organisation CURhE, a group of physicians in Africa, India, the United States and Canada, who fights the so-called rhesus disease. In Denmark it is unknown, but it is a disease of neonates, which is due to the fact that a rhesus negative mother forms antibodies to the red blood cells of a rhesus positive foetus.

"It does not have great significance for the first child a woman is pregnant with. However, if she becomes pregnant again, she may have a miscarriage, which can be dangerous in India or Africa. Subsequent pregnancies could also end with brain damage in newborns or stillbirth. In our part of the world, this is treated with an infusion of special antibodies. But this is not automatically done in e.g. Africa," says Kasper Juul Hedegaard from Eldon Biologicals.

CURhE is run by researchers at Stanford University, and they have particularly called for a digitisation of the cards. The application allows for the collection of statistical data and for sending the result to the local blood banks. At the same time, it is possible to send a text message with the blood type to the woman.

The collaboration is carried out under the Videnkupon programme (now InnoBooster programme) under Innovation Fund Denmark.

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