  Thalassaemia, triggered by defects in the globin genes, is one of the most
common monogenic diseases. The beta-thalassaemia carrier state is clinically
asymptomatic, thus, making it onerous to diagnose. The current gold standard
technique is implausible to be used for onsite carrier detection as the method
necessitates expensive instruments, skilled manpower and time. In this study,
we have tried to classify the carriers from the healthy samples based on their
blood droplet drying patterns using image analysis based tools and subsequently
develop an in-house program for automated classification of the same. This
automatic, rapid, less laborious and cost-effective technique will
significantly increase the total number of carriers that are screened for
thalassaemia per year in the country, thus, reducing the burden in the state
run advanced health facilities.
