A novel retinal vessel detection approach based on multiple deep convolution neural networks

Guo Yanhui; Budak Umit; Sengur Abdulkadir

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A novel retinal vessel detection approach based on multiple deep convolution neural networks

机译：一种基于多个深层卷积神经网络的新型视网膜检测方法

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摘要

Background and objective: Computer aided detection (CAD) offers an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is a crucial step to identify the retinal disease regions. However, RV detection is still a challenging problem due to variations in morphology of the vessels on noisy and low contrast fundus images.

机译：背景和目的：计算机辅助检测（CAD）提供了一种有效的方法来帮助医生解释眼底图像。在CAD系统中，视网膜血管（RV）检测是鉴定视网膜疾病区域的关键步骤。然而，由于噪声和低对比度眼底图像的血管形态的变化，RV检测仍然是一个具有挑战性的问题。

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《Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice》 |2018年第2018期|共6页
作者
Guo Yanhui; Budak Umit; Sengur Abdulkadir;
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作者单位

Univ Illinois Dept Comp Sci Springfield IL 62703 USA;

Bitlis Eren Univ Dept Elect Elect Engn Bitlis Turkey;

Firat Univ Elect &

Elect Engn Dept Elazig Turkey;

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原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
关键词
Retinal vessels segmentation; Multiple deep convolution neural network; Image segmentation;

机译：视网膜血管分割;多个深卷积神经网络;图像分割;

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1. A novel retinal vessel detection approach based on multiple deep convolution neural networks [J] . Guo Yanhui, Budak Umit, Sengur Abdulkadir Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice . 2018,第期

机译：一种基于多个深层卷积神经网络的新型视网膜检测方法
2. Retinal Vessel Segmentation based on Convolutional Neural Network and Connection Domain Detection [J] . Quansheng Dou, Jiayuan Zhang, Ping Jiang, Procedia Computer Science . 2021,第a期

机译：基于卷积神经网络和连接域检测的视网膜血管分割
3. A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset [J] . Espinosa Ricardo, Ponce Hiram, Gutierrez Sebastian, Computers in Biology and Medicine . 2019,第期

机译：使用多个摄像机和卷积神经网络的坠落检测的基于视觉检测方法：一种使用上落检测数据集的案例研究
4. Retinal Vessel Detection in Wide-Field Fluorescein Angiography with Deep Neural Networks: A Novel Training Data Generation Approach [C] . Li Ding, Ajay Kuriyan, Rajeev Ramchandran, IEEE International Conference on Image Processing . 2018

机译：带有深层神经网络的广域荧光素血管造影术中的视网膜血管检测：一种新型的训练数据生成方法
5. Deep Neural Language Model for Text Classification Based on Convolutional and Recurrent Neural Networks [D] . Hassan, Abdalraouf. 2018

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6. A Deep Learning-Based Approach for the Detection of Early Signs of Gingivitis in Orthodontic Patients Using Faster Region-Based Convolutional Neural Networks [O] . Dima M. Alalharith, Hajar M. Alharthi, Wejdan M. Alghamdi, 2020

机译：基于速度基于区域的卷积神经网络的正畸患者在正畸患者中检测早期学习的方法
7. A Fully Convolutional Neural Network based Structured Prediction Approach Towards the Retinal Vessel Segmentation [O] . Dasgupta Avijit, Singh Sonam 2016

机译：基于完全卷积神经网络的结构预测视网膜血管分割的探讨

A novel retinal vessel detection approach based on multiple deep convolution neural networks

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