Abstract: A method for early diagnosis of keratoconus based on multi-modal data considers a mutual relationship between both eyes using four refractive maps for corneas of the both eyes and absolute corneal elevation data, and combines the deep convolutional network method, the traditional support vector machine (SVM) method in machine learning, and the elevation map enhancement method with adjustable best-fit-sphere (BFS) to identify sensitivity and specificity of a focus and balance the sensitivity and specificity. With multi-dimensional comprehensive judgment of a keratoconus morbidity with a patient as a unit, combined with binocular data including both manual selection features and deep network learning from big data, the diagnosis method has higher robustness and accuracy.

Abstract: A method for early diagnosis of keratoconus based on multi-modal data considers a mutual relationship between both eyes using four refractive maps for corneas of the both eyes and absolute corneal elevation data, and combines the deep convolutional network method, the traditional support vector machine (SVM) method in machine learning, and the elevation map enhancement method with adjustable best-fit-sphere (BFS) to identify sensitivity and specificity of a focus and balance the sensitivity and specificity. With multi-dimensional comprehensive judgment of a keratoconus morbidity with a patient as a unit, combined with binocular data including both manual selection features and deep network learning from big data, the diagnosis method has higher robustness and accuracy.

Abstract: An eye imaging system, including: a light source module; a radial splitting module; a common optical module; an image receiver; a power supply module for the light source module; a driver module for the image receiver; a processing-displaying module; and a motion driving module. The image receiver is an area array sensor. The motion driving module is connected to the light source module and drives the light source module to move in a radial direction of an upstream illuminating optical path formed by the light source module and the radial splitting module. The image receiver continually opens for exposure in a radial direction of a downstream observation optical path formed by the radial splitting module and the image receiver. The continual opening of the image receiver for signal acquisition is synchronous with the movement of the light source module.

Abstract: An eye imaging system, including: a light source module; a radial splitting module; a common optical module; an image receiver; a power supply module for the light source module; a driver module for the image receiver; a processing-displaying module; and a motion driving module. The image receiver is an area array sensor. The motion driving module is connected to the light source module and drives the light source module to move in a radial direction of an upstream illuminating optical path formed by the light source module and the radial splitting module. The image receiver continually opens for exposure in a radial direction of a downstream observation optical path formed by the radial splitting module and the image receiver. The continual opening of the image receiver for signal acquisition is synchronous with the movement of the light source module.