Pathological Myopia Image Analysis Using Deep Learning

Author:

Devda Jaydeep,Eswari R.

Publisher

Elsevier BV

Subject

General Engineering

Reference7 articles.

1. Wong, Joo Hwee Lim, et al., “Detection of Pathological Myopia by PAMELA with Texture-Based Features through an SVM Approach,”;Liu;Journal of Healthcare Engineering,2010

2. "Understanding of a convolutional neural network," 2017 International Conference on Engineering and Technology (ICET);Albawi;Antalya,2017

3. Zhang, Zhuo & Xu, Yanwu & Liu, Jiang & Wing Kee Wong, Damon & Kwoh, Chee-Keong & Saw, Seang-Mei & Wong, T-Y. (2013). Automatic Diagnosis of Pathological Myopia from Heterogeneous Biomedical Data.

4. "Fundus image analysis for detection of fovea: A review," 2017 International Conference on Intelligent Computing and Control (I2C2);Joshi;Coimbatore,2017

5. U-net: Convolutional networks for biomedical image segmentation, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 (Cham) (Nassir Navab, Joachim Hornegger, William M. Wells, and Alejandro F. Frangi, eds.);Ronneberger,2015

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