Abstract
BackgroundStudies on malaria vector ecology and development/evaluation of vector control strategies often require measures of mosquito life history traits. Assessing the fecundity of malaria vectors can be carried out by counting eggs laid by Anopheles females. However, manually counting the eggs is time consuming, tedious, and error prone.MethodsIn this paper we present a newly developed software for high precision automatic egg counting. The software written in the Java programming language proposes a user-friendly interface and a complete online manual. It allows the inspection of results by the operator and includes proper tools for manual corrections. The user can in fact correct any details on the acquired results by a mouse click. Time saving is significant and errors due to loss of concentration are avoided.ResultsThe software was tested over 16 randomly chosen images from 2 different experiments. The results show that the proposed automatic method produces results that are close to the ground truth.ConclusionsThe proposed approaches demonstrated a very high level of robustness. The adoption of the proposed software package will save many hours of labor to the bench scientist. The software needs no particular configuration and is freely available for download on: http://w3.ualg.pt/∼hshah/eggcounter/.
Highlights
Studies on malaria vector ecology and development/evaluation of vector control strategies often require measures of mosquito life history traits
Understanding the ecology and evolution of malaria vector species and populations is a key factor in controlling the disease they carry [1]
More directly related to vector control, fitness measures can help deciphering the effect of insecticides [14], including new classes of insect growth regulators [15], effect of insecticide resistance [16,17], genetic manipulation of vector populations to make them resistant to parasites [18,19], or to impede their reproductive success
Summary
As it is shown eggs and debris are properly extracted, after the automatic threshold is found. The accumulative ratio is necessary due to the fact that regions in the intersection of the eggs inside a pile are shadowed by the eggs and are usually considered as a connected object in the binary map. Multiplying by this ratio allows better estimation of the number of eggs. After the user opens an image, the software automatically computes the threshold value, detects and removes areas of debris, estimates the number of eggs inside each pile of the eggs and removes the noise. Corrections are mainly required on the debris areas without enough colorful pixels beside them, and eggs that fall in the neighborhood of debris areas
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