Automatic localization of macular area based on structure label transfer

作     者：Xiao-Xin Guo Qun Li Chao Sun Yi-Nan LU 

作者机构：Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun130012 Jilin Province China College of Computer Science and Technology Jilin University Changchun 130012 Jilin Province China 

出 版 物：《International Journal of Ophthalmology(English edition)》 (国际眼科杂志（英文版）)

年 卷 期：2018年第11卷第3期

页      面：422-428页

核心收录：

学科分类：1002[医学-临床医学] 100212[医学-眼科学] 10[医学] 

基　　金：Supported by the National Key Research and Development Program of China(No.2016YFB0201503,No.2017YFC0602203) the 13th Five-Year Plan of the Science and Technology Research of the Education Department of Jilin Province(No.2016433) the National Natural Science Foundation of China(No.60905022) the Ph D.Program Foundation of the Ministry of Education of China(No.20130061110054) 

主　　题：fundus image optic disc macula structurelabel transfer 

摘      要：AIM： To explore feasibility and practicability of macula localization independent of macular morphological features. METHODS： A novel method was proposed to identify macula in fundus images by using structure label transfer. Its main idea was to match a processed image with the candidate images with known structures, and then transfer the structure label representing the macular to the processed image as a result of macula localization. In this way, macula localization couldn＇t be influenced by lesion or other interference any more. RESULTS： The average success rate in four datasets was 98.18%. For accuracy, the average error distance in four datasets was 0.151 optic disc diameter （ODD）. Even for severe lesion images, the proposed method can still maintain high success rate and high accuracy, e.g., 95.65% and 0.124 ODD in the case of STARE dataset, respectively, which indicated that the proposed method was highly robust and stable in the complicated situations. CONCLUSION： The proposed method can avoid the interference of lesion to macular morphological features in macula localization, and can locate macula with high accuracy and robustness, verifying its feasibility.