Abstract
Cataract is one of the most common eye disorders that causes vision distortion. Accurate and timely detection of cataracts is the best way to control the risk and avoid blindness. Recently, artificial intelligence-based cataract detection systems have been received research attention. In this paper, a novel deep neural network, namely CataractNet , is proposed for automatic cataract detection in fundus images. The loss and activation functions are tuned to train the network with small kernels, fewer training parameters, and layers. Thus, the computational cost and average running time of CataractNet are significantly reduced compared to other pre-trained Convolutional Neural Network (CNN) models. The proposed network is optimized with the Adam optimizer. A total of 1130 cataract and non-cataract fundus images are collected and augmented to 4746 images to train the model. For avoiding the over-fitting problem, the dataset is extended through augmentation before model training. Experimental results prove that the proposed method outperforms the state-of-the-art cataract detection approaches with an average accuracy of 99.13%.
Highlights
Cataract is a lenticular opacity clouding the transparent lens in human eyes
AND DISCUSSIONS we discuss the performance of the proposed CataractNet
FIGURE2: Confusion Matrix of the proposed CataractNet and F1-Score are successful metrics that are calculated by averaging the results of the performance verification
Summary
Cataract is a lenticular opacity clouding the transparent lens in human eyes. Typically, the lens converges the light to the retina. The presence of the cataract causes this light to be blocked and not reach the lens that results in poor visual acuity. It is a worldwide leading eye disease that develops gradually and does not affect sight early. The world health organization (WHO) reported [3] that about 285 million people in the world have a visual impairment. 39 million people are blind, and the remaining ones have impaired vision. In 2020, Flaxman et al [5] predicted that the number of people suffering from moderate to severe vision impairment (MSVI) and blindness would be 237.1 and 38.5 million, respectively. The worldwide blindness will exceed 40 million by 2025 [6]
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