title: [Application of improved PCNN algorithm in retinal macular edema segmentation].
abstract: In order to extract the outlines of macular edema from OCT images of macular, and estimate the volume of edema, we have to accurately segment the macular edema region. In this paper, an improved PCNN algorithm was proposed to conduct the above process. Combined with the adaptive base threshold, and the simplified neural network parameters, a binary image of macular edema was produced. According to the principle of maximum image entropy, the optimal number of iterations was determined as 8, which was evaluated by its misclassification rate. Simulation showed that the proposed algorithm could extract the macular edema region rapidly and accurately, providing the basis for further OCT image analysis.
authors: The 5th Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000. xiezhn@mail.sysu.edu.cn
authors: Zhinan
authors: Z
authors: Xie
authors: Min
authors: M
authors: Gu
authors: Yixiao
authors: Y
authors: Wu
authors: Dong
authors: D
authors: Zheng
mesh_terms: D000465:Algorithms; D005451:Fluorescein Angiography / Q000379:methods*; D006801:Humans; D008269:Macular Edema / Q000000981:diagnostic imaging*; D011859:Radiography; D041623:Tomography, Optical Coherence / Q000379:methods*