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- 出生日期：1983-09-02
- 电子邮箱：zhaowang92@uestc.edu.cn
- 入职时间：2018-06-01
- 学历：博士研究生毕业
- 办公地点：清水河科研楼4号C区336房间
- 性别：男
- 学位：哲学博士学位
- 职称：教授
- 博士生导师
- 曾获荣誉：国家青年特聘专家，荣获四川省“天府峨眉计划”、成都市“四派人才”、“蓉漂计划”称号
- 学科：电子科学与技术
物理电子学
ECLNet: Center localization of eye structures based on Adaptive Gaussian Ellipse Heatmap
- 点击次数：
- 所属单位：[1]Taiyuan Univ Technol, Coll Elect & Power Engn, Taiyuan 030024, Peoples R China;[2]Univ Elect Sci & Technol China, Sch Elect Sci & Engn, Chengdu 611731, Peoples R China;[3]Beijing Univ Chinese Med, Affiliated Hosp 3, Beijing 100029, Peoples R China;[4]Taiyuan Univ Technol, Coll Informat & Comp, Jinzhong 030600, Peoples R China
- 发表刊物：COMPUTERS IN BIOLOGY AND MEDICINE
- 关键字：Deep learning; Center localization; Gaussian heatmap; Medical image
- 摘要：Accurately localizing the center of specific biological structures in medical images is of great significance for clinical treatment. The center localization task can be viewed as an estimation problem of keypoints, and the heatmap is often used to describe the probability of the location of keypoints during estimation. Existing methods construct the heatmap from a Gaussian kernel function with a fixed standard deviation, therefore cannot adapt to morphologic changes of the target region. In this paper, we build a deep network, ECLNet, to localize the center of eye-related structures in medical images. Meanwhile, we propose a method called Adaptive Gaussian Ellipse Heatmap (AGEH), which can efficiently utilize the gradient feature of the target region to adjust the morphology of the heatmap. The ECLNet localizes the optic disc and fovea center with mean Euclidean Distance of 17.995 and 39.446 pixels, respectively, for IDRiD dataset. The ECLNet also successfully localizes the eye center with the mean absolute Position Error of 0.186 +/- 0.027 mm for CATARACT dataset. The results show that our proposed method has a better performance compared with some state-of-the-art methods.
- 文献类型：Article
- 卷号：153
- ISSN号：0010-4825
- 是否译文：否