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Automated fundus image quality assessment and segmentation of optic disc using convolutional neural networks

机译：使用卷积神经网络自动化眼底图像质量评估和光盘分割

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Bhargav Bhatkalkar; Abhishek Joshi; Srikanth Prabhu; Sulatha Bhandary;
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年度 2020
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1. Automated fundus image quality assessment and segmentation of optic disc using convolutional neural networks [J] . Bhargav Bhatkalkar, Abhishek Joshi, Srikanth Prabhu, International Journal of Electrical and Computer Engineering . 2020,第1期

机译：使用卷积神经网络自动化眼底图像质量评估和光盘分割
2. Improving the Performance of Convolutional Neural Network for the Segmentation of Optic Disc in Fundus Images Using Attention Gates and Conditional Random Fields [J] . Bhatkalkar Bhargav J., Reddy Dheeraj R., Prabhu Srikanth, Quality Control, Transactions . 2020,第期

机译：使用注意门和条件随机字段提高眼底图像中光盘分割的卷积神经网络的性能
3. A Novel Intensity Weighting Approach Using Convolutional Neural Network for Optic Disc Segmentation in Fundus Image [J] . Kim Ga Young, Lee Sang Hyeok, Kim Sung Min Journal of Imaging Science and Technology . 2020,第4期

机译：一种新颖的强度加权方法，使用卷积神经网络在眼底图像中的光盘分割
4. Optic disc boundary segmentation from diffeomorphic demons registration of monocular fundus image sequences vs. 3-D visualization of stereo fundus image pairs for automated early stage glaucoma assessment [C] . Vijay Gatti, Jason Hill, Sunanda Mitra, Conference on biomedical applications in molecular, structural, and functional imaging . 2014

机译：来自单眼底图像序列的变态恶魔配准的视盘边界分割与立体眼底图像对的3-D可视化以进行自动化早期青光眼评估
5. Automated Segmentation and Uncertainty Quantification for Image-Based Cardiovascular Modeling with Convolutional Neural Networks [D] . Maher, Gabriel. 2020

机译：卷积神经网络的图像基础心血管建模的自动分割和不确定量化
6. Graph convolutional network based optic disc and cup segmentation on fundus images [O] . Zhiqiang Tian, Yaoyue Zheng, Xiaojian Li, 2020

机译：基于图卷积网络的视盘和眼底图像杯分割
7. Automated Fundus Image Quality Assessment in Retinopathy of Prematurity Using Deep Convolutional Neural Networks [O] . Aaron S. Coyner, Ryan Swan, J. Peter Campbell, 2019

机译：使用深卷积神经网络，自动化眼底图像质量评估在早产度的视网膜病变

Automated fundus image quality assessment and segmentation of optic disc using convolutional neural networks

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