Fully Automated Tree Topology Estimation and Artery-Vein Classification
- URL: http://arxiv.org/abs/2202.02382v1
- Date: Fri, 4 Feb 2022 20:40:01 GMT
- Title: Fully Automated Tree Topology Estimation and Artery-Vein Classification
- Authors: Aashis Khanal, Saeid Motevali, and Rolando Estrada
- Abstract summary: We present a fully automatic technique for extracting the retinal vascular topology, i.e., how the different vessels are connected to each other, given a single color fundus image.
We validated the usefulness of our extraction method by using it to achieve state-of-the-art results in retinal artery-vein classification.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We present a fully automatic technique for extracting the retinal vascular
topology, i.e., how the different vessels are connected to each other, given a
single color fundus image. Determining this connectivity is very challenging
because vessels cross each other in a 2D image, obscuring their true paths. We
validated the usefulness of our extraction method by using it to achieve
state-of-the-art results in retinal artery-vein classification.
Our proposed approach works as follows. We first segment the retinal vessels
using our previously developed state-of-the-art segmentation method. Then, we
estimate an initial graph from the extracted vessels and assign the most likely
blood flow to each edge. We then use a handful of high-level operations (HLOs)
to fix errors in the graph. These HLOs include detaching neighboring nodes,
shifting the endpoints of an edge, and reversing the estimated blood flow
direction for a branch. We use a novel cost function to find the optimal set of
HLO operations for a given graph. Finally, we show that our extracted vascular
structure is correct by propagating artery/vein labels along the branches. As
our experiments show, our topology-based artery-vein labeling achieved
state-of-the-art results on multiple datasets. We also performed several
ablation studies to verify the importance of the different components of our
proposed method.
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