Automatic Feature Learning for Glaucoma Detection Based on Deep Learning
Glaucoma is a chronic and irreversible eye disease in which the optic nerve is progressively damaged, leading to deterioration in vision and quality of life. In this paper, we present an Automatic feature Learning for glAucoma Detection based on Deep Lear
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Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore 2 Department of Electrical and Computer Engineering, National University of Singapore Department of Ophthalmology, National University of Singapore
Abstract. Glaucoma is a chronic and irreversible eye disease in which the optic nerve is progressively damaged, leading to deterioration in vision and quality of life. In this paper, we present an Automatic feature Learning for glAucoma Detection based on Deep LearnINg (ALADDIN), with deep convolutional neural network (CNN) for feature learning. Different from the traditional convolutional layer that uses linear filters followed by a nonlinear activation function to scan the input, the adopted network embeds micro neural networks (multilayer perceptron) with more complex structures to abstract the data within the receptive field. Moreover, a contextualizing deep learning structure is proposed in order to obtain a hierarchical representation of fundus images to discriminate between glaucoma and non-glaucoma pattern, where the network takes the outputs from other CNN as the context information to boost the performance. Extensive experiments are performed on the ORIGA and SCES datasets. The results show area under curve (AUC) of the receiver operating characteristic curve in glaucoma detection at 0.838 and 0.898 in the two databases, much better than state-of-the-art algorithms. The method could be used for glaucoma diagnosis.
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Introduction
Glaucoma is a chronic eye disease that leads to vision loss, in which the optic nerve is progressively damaged. It is one of the common causes of blindness, and is predicted to affect around 80 million people by 2020 [8]. Glaucoma is characterized by the progressive degeneration of optic nerve fibres, which leads to structural changes of the optic nerve head, the nerve fibre layer and a simultaneous functional failure of the visual field. As the symptoms only occur when the disease is quite advanced, glaucoma is called the silent thief of sight. Although glaucoma cannot be cured, its progression can be slowed down by treatment. Therefore, timely diagnosis of this disease is important. Glaucoma diagnosis is typically based on the medical history, intra-ocular pressure and visual field loss tests together with a manual assessment of the Optic c Springer International Publishing Switzerland 2015 N. Navab et al. (Eds.): MICCAI 2015, Part III, LNCS 9351, pp. 669–677, 2015. DOI: 10.1007/978-3-319-24574-4_80
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X. Chen et al.
Disc (OD) through ophthalmoscopy. OD or optic nerve head is the location where ganglion cell axons exit the eye to form the optic nerve, through which visual information of the photo-receptors is transmitted to the brain. In 2D images, the OD can be divided into two distinct zones; namely, a central bright zone called the optic cup (in short, cup) and a peripheral region called the neuroretinal rim. The loss in optic nerve fibres leads to a change in the structural appearance of the OD, namely, the enlargement of cup region (thin
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