Towards End-to-End Image-to-Tree for Vasculature ModelingDownload PDF

11 Apr 2019 (modified: 13 Jun 2019)MIDL 2019 Conference Abstract SubmissionReaders: Everyone
  • Keywords: Vasculature, tree extraction, retinal vessels, diabetic retinopathy, visualization
  • TL;DR: Extracting tree from medical image scans, and showing how they can be used/visualized.
  • Abstract: This work explores an end-to-end image-to-tree approach for extracting accurate representations of vessel structures which may be beneficial for diagnosis of stenosis (blockages) and modeling of blood flow. Current image segmentation approaches capture only an implicit representation, while this work utilizes a subscale U-Net to extract explicit tree representations from vascular scans. We obtain insights from these representations by associating tubular thickness with tree edges and visualizing the network of blood vessels from the Digital Retinal Vessel Extraction dataset (DRIVE).
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