Tsinghua University

Zhongshan Ophthalmic Center, Sun Yat-sen University

Zhongshan Ophthalmic Center of Sun Yat-sen University

Haotian Lin

Feng Xu

Junfeng Lyu

Ruixin Wang

Weiyi Lai

Xiaohang Wu

Yahan Yang

Xinping Yu

Disclosed are a method and apparatus for measuring a gaze difference based on gaze estimation. Video data of a testee gazing at a visual target is obtained, and a face image sequence is obtained from the video data. The face image sequence is input into a first neural network for key frame extraction to obtain a first and second gaze position face image. The face images are input into a second neural network for facial feature point extraction. Cropping is performed based on facial feature point coordinates to obtain a first and second eye region image. A gaze difference estimation network is trained to obtain a trained gaze difference estimation network. The first and second eye region images are input into the trained gaze difference estimation network to obtain a predicted gaze difference between the first and second eye region images.

Method and apparatus for measuring gaze difference based on gaze estimation

A method and an apparatus for protecting privacy of an ophthalmic patient and a storage medium are disclosed. The method includes: acquiring an examination video of the ophthalmic patient; extracting image features of each frame of images in the examination video, performing region division on each frame of the images according to position information of organs in the image features, and obtaining a region to be precisely reconstructed and a region to be roughly reconstructed according to a region division result; performing three-dimensional (3D) reconstruction on the region to be precisely reconstructed and the region to be roughly reconstructed, to obtain 3D reconstruction data corresponding to each frame of the images; and rendering all the 3D reconstruction data into a 3D reconstruction video.

Method and apparatus for protecting privacy of ophthalmic patient and storage medium

The invention relates to an artificial intelligence cataract analysis system, including a pattern recognition module for recognizing a photo mode of an input eye image, wherein the photo mode is divided according to the slit width of the illuminating slit during photographing of the eye image and/or whether a mydriatic treatment is carried out; a preliminary analysis module used for selecting a corresponding deep learning model for eye different photo modes, analyzing the characteristics of lens in the eye image by using a deep learning model, and further performing classification in combination with cause and severity degree of a disease. The invention can perform cataract intelligent analysis on eye images with different photo modes by using deep learning models, so that the analysis accuracy is improved.

Artificial intelligence cataract analysis system

Growing community of inventors

Guangdong, China

Haotian Lin