Abstract
Eye is one of the most vital organs of human body. Despite being small in size, humans cannot see the life around them without it. Human eye is protected by a thin covering termed as conjunctiva which protects the eye from dust particles. It plays the role of lubricant in the eye which prevents any sort of friction in opening and closing of eye. Broadly there are two kinds of conjunctiva: bulbar and palpebral. The membrane covering the inner portion of eyelids is termed as palpebral conjunctiva and the one covering the outside portion of the eye is called as bulbar conjunctiva (white portion of eye).Due to the dilation of blood vessels the white portion of the eye also termed as sclera becomes red in color. This condition is also termed as hyperemia. The study of this development is vital in diagnosis of various pathologies. It could be result of some trauma, injury or other eye related diseases which needs to be identified for timely treatment. Enormous amount of studies have been done to study the structure and functionality of human eye. This paper highlights the work done so far for measuring the level of redness in the eye using various methodologies ranging from statistical ways to machine learning techniques and proposes a methodology using Matlab and Convolutional neural network to automate this evaluation process.
Highlights
Conjunctival Hyperemia results due to the engorgement of blood vessel in the sclera of the eye
This scale highlighted the clinical performance of lenses with respect to short and prolonged use [15] [16]. It graded the bulbar redness on a 5-point photographic scale where 1 stands for very slight, 2 means slight, 3 signifies moderate and 4 represents the condition as severe. The results of this scale lacked in homogeneity, either in terms of different www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Vol 10, No 7, 2019 illumination conditions or variability of size of the area under display.Later Efron grading scale was developed which graded the severity of hyperemia on the scale of 0 to 4 [17]
1) Convolutional neural network: Convolutional neural network is a special kind of neural network which can work on images ranging from one dimensional, two dimensional to three dimensional
Summary
Conjunctival Hyperemia results due to the engorgement of blood vessel in the sclera of the eye. The accurate interpretation of bulbar redness can identify various pathologies like morning eye congestion, bacterial conjunctivitis, dry eye [2], trauma due to prolonged use of contact lenses, iritis and other severe infections [1][3]. It is a well know side effect of glaucoma treatment [4].Because of these symptoms, patients suffering from the glaucoma drugs often discontinue the treatment [5].Timely and correct diagnosis of these conditions can further reduce any damage to the eye and help in treatment plan.
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