scholarly journals Weakly supervised retinal vessel segmentation algorithm without groundtruth

2020 ◽  
Vol 56 (23) ◽  
pp. 1235-1237
Author(s):  
Zheng Lu ◽  
Dali Chen ◽  
Dingyu Xue
Keyword(s):  
Retinal Vessel ◽  
Vessel Segmentation ◽  
Segmentation Algorithm ◽  
Retinal Vessel Segmentation ◽  
Weakly Supervised

U-Shaped Retinal Vessel Segmentation Algorithm Based on Adaptive Scale Information

2019 ◽  
Vol 39 (8) ◽  
pp. 0810004 ◽  
Author(s):  
梁礼明 Liang Liming ◽  
盛校棋 Sheng Xiaoqi ◽  
蓝智敏 Lan Zhimin ◽  
杨国亮 Yang Guoliang ◽  
陈新建 Chen Xinjian
Keyword(s):  
Retinal Vessel ◽  
Vessel Segmentation ◽  
Segmentation Algorithm ◽  
Retinal Vessel Segmentation

scholarly journals Retinal Vessel Segmentation Algorithm Based on Residual Convolution Neural Network

2021 ◽  
Vol 9 ◽  
Author(s):  
Shuang Xu ◽  
Zhiqiang Chen ◽  
Weiyi Cao ◽  
Feng Zhang ◽  
Bo Tao
Keyword(s):  
Neural Network ◽  
Retinal Vessel ◽  
Vessel Segmentation ◽  
Segmentation Algorithm ◽  
Convolution Neural Network ◽  
Superior Performance ◽  
Retinal Vessels ◽  
Fundus Images ◽  
Data Set ◽  
Retinal Vessel Segmentation

Retinal vessels are the only deep micro vessels that can be observed in human body, the accurate identification of which has great significance on the diagnosis of hypertension, diabetes and other diseases. To this end, a retinal vessel segmentation algorithm based on residual convolution neural network is proposed according to the characteristics of the retinal vessels on fundus images. Improved residual attention module and deep supervision module are utilized, in which the low-level and high-level feature graphs are joined to construct the encoder-decoder network structure, and atrous convolution is introduced to the pyramid pooling. The experiments result on the fundus image data set DRIVE and STARE show that this algorithm can obtain complete retinal vessel segmentation as well as connected vessel stems and terminals. The average accuracy on DRIVE and STARE reaches 95.90 and 96.88%, and the average specificity is 98.85 and 97.85%, which shows superior performance compared to other methods. This algorithm is verified feasible and effective for retinal vessel segmentation of fundus images and has the ability to detect more capillaries.

Boosting sensitivity of a retinal vessel segmentation algorithm

2017 ◽  
Vol 22 (2) ◽  
pp. 583-599 ◽  
Author(s):  
Mohammad A. U. Khan ◽  
Tariq M. Khan ◽  
Toufique Ahmed Soomro ◽  
Nighat Mir ◽  
Junbin Gao
Keyword(s):  
Retinal Vessel ◽  
Vessel Segmentation ◽  
Segmentation Algorithm ◽  
Retinal Vessel Segmentation

scholarly journals A proposal to measure the similarity between retinal vessel segmentations images

Nova Scientia ◽  
2019 ◽  
Vol 11 (22) ◽  
pp. 224-245 ◽  
Author(s):  
Marco A. Escobar ◽  
José R. Guzmán Sepúlveda ◽  
Jorge R. Parra Michel ◽  
Rafael Guzmán Cabrera
Keyword(s):  
Fractal Dimension ◽  
Structural Properties ◽  
Strong Correlation ◽  
Performance Metrics ◽  
Automatic Segmentation ◽  
Retinal Vessel ◽  
Vessel Segmentation ◽  
Segmentation Algorithm ◽  
Novel Approach ◽  
Retinal Vessel Segmentation

Introduction: We propose a novel approach for the assessment of the similarity of retinal vessel segmentation images that is based on linking the standard performance metrics of a segmentation algorithm, with the actual structural properties of the images through the fractal dimension.Method: We apply our methodology to compare the vascularity extracted by automatic segmentation against manually segmented images.Results: We demonstrate that the strong correlation between the standard metrics and fractal dimension is preserved regardless of the size of the subimages analyzed.Discussion or Conclusion: We show that the fractal dimension is correlated to the segmentation algorithm’s performance and therefore it can be used as a comparison metric.

A high resolution representation network with multi-path scale for retinal vessel segmentation

2021 ◽  
pp. 106206
Author(s):  
Zefang Lin ◽  
Jianping Huang ◽  
Yingyin Chen ◽  
Xiao Zhang ◽  
Wei Zhao ◽  
...  
Keyword(s):  
High Resolution ◽  
Retinal Vessel ◽  
Vessel Segmentation ◽  
Retinal Vessel Segmentation
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