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1. (WO2018201632) ARTIFICIAL NEURAL NETWORK AND SYSTEM FOR RECOGNIZING LESION IN FUNDUS IMAGE

Pub. No.:    WO/2018/201632    International Application No.:    PCT/CN2017/095909
Publication Date: Fri Nov 09 00:59:59 CET 2018 International Filing Date: Sat Aug 05 01:59:59 CEST 2017
IPC: G06T 7/00
Applicants: SHENZHEN SIBIONICS TECHNOLOGY CO., LTD.
深圳硅基仿生科技有限公司
SHENZHEN SIBRIGHT TECHNOLOGY CO., LTD.
深圳硅基智能科技有限公司
Inventors: WANG, Juan
王娟
XIA, Bin
夏斌
BAI, Yujing
白玉婧
LI, Xiaoxin
黎晓新
HU, Zhigang
胡志钢
ZHAO, Yu
赵瑜
Title: ARTIFICIAL NEURAL NETWORK AND SYSTEM FOR RECOGNIZING LESION IN FUNDUS IMAGE
Abstract:
An artificial neural network system for recognizing a lesion in a fundus image, comprising: a pre-processing module, configured for pre-processing a target fundus image and a reference fundus image of the same person; a first neural network (12), configured to generate a first advanced feature set from the target fundus image; a second neural network (22), configured to generate a second advanced feature set from the reference fundus image; a feature combination module (13), configured to merge the first advanced feature set and the second advanced feature set to form a feature combination set; and a third neural network (14), configured to generate, according to the feature combination set, a judgment result of the lesion. The present invention uses a target fundus image and a reference fundus image as independent input information, and can thus stimulate a diagnostic process of a doctor to judge the target fundus image with reference to other fundus images of the same person, facilitating in improving the accuracy of judgment of the lesion from the fundus images.