文献类型： 外文期刊

作者： Tian, Shu ¹ ; Yin, Xu-Cheng ¹ ; Wang, Zhi-Bin ² ; Zhou, Fang ¹ ; Hao, Hong-Wei ³ ;

作者机构： 1.Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Dept Comp Sci & Technol, Beijing 100083, Peoples R China

2.Natl Engn Res Ctr Informat Technol Agr, Beijing 100089, Peoples R China

3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China

期刊名称：COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE （ 影响因子：2.238； 五年影响因子：2.477 ）

ISSN： 1748-670X

年卷期： 2015 年

页码：

收录情况： SCI

摘要： The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness.