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: The present invention includes: receiving an optical signal from a transmission link via an STM-4 optical port; converting the received optical signal into an electrical signal; recovering an E1 signal; performing HDLC link deframe mapping, removing a frame header and an interpolated zero part in the HDLC link, and extracting the payload of a sliced HDLC packet; and processing and outputting a received HDLC data stream to a host. The present invention further provides a device for acquiring data via a channelized optical port STM-4 HDLC according to the method for acquiring data via a channelized optical port STM-4 HDLC.

Abstract: The present invention provides a method and device for acquiring data via a channelized optical port STM-4 HDLC, the method comprising: receiving an optical signal from a transmission link via an STM-4 optical port; converting the received optical signal into an electrical signal; recovering an E1 signal by means of signal processing; performing HDLC link deframe mapping, removing a frame header and an interpolated zero part in the HDLC link, and extracting the payload of a sliced HDLC packet; and processing and outputting a received HDLC data stream to a host. The present invention further provides a device for acquiring data via a channelized optical port STM-4 HDLC according to the method for acquiring data via a channelized optical port STM-4 HDLC.