A Hierarchical Image Matting Model for Blood Vessel Segmentation in Fundus Images

@article{Fan2019AHI,
  title={A Hierarchical Image Matting Model for Blood Vessel Segmentation in Fundus Images},
  author={Zhun Fan and Jiewei Lu and Caimin Wei and Han Huang and Xinye Cai and Xinjian Chen},
  journal={IEEE Transactions on Image Processing},
  year={2019},
  volume={28},
  pages={2367-2377}
}
In this paper, a hierarchical image matting model is proposed to extract blood vessels from fundus images. More specifically, a hierarchical strategy is integrated into the image matting model for blood vessel segmentation. Normally, the matting models require a user specified <italic>trimap</italic>, which separates the input image into three regions: the foreground, background, and unknown regions. However, creating a user specified trimap is laborious for vessel segmentation tasks. In this… 
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70 Citations

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Robust retinal blood vessel segmentation using hybrid active contour model

This study presents a hybrid active contour model with a novel preprocessing technique to segment the retinal blood vessel in different fundus images by calculating a wide range of proven parameters to prove its robustness.

Retinal Blood Vessels Segmentation using ISODATA and High Boost Filter

A robust vessel segmentation algorithm that is efficient enough to segment retinal vessels tree automatically and accurately and outperforms recently published methods in terms of statistical parameters, such as Accuracy, Sensitivity, and Specificity on DRIVE and STARE datasets.

A Multilevel Remote Relational Modeling Network for Accurate Segmentation of Fundus Blood Vessels

A novel multilevel remote relational modeling network (MRRM-Net) is proposed, which can balance global/local long-range contextual relations through building multidimensional and multileVEL attention and has more robust data adaptability than other state-of-the-art network structures in a small capacity.

Retinal blood vessel segmentation in fundus images based on morphological operators within entropy information

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