A Hybrid Approach to Full-Scale Reconstruction of Renal Arterial Network
- URL: http://arxiv.org/abs/2303.01837v1
- Date: Fri, 3 Mar 2023 10:39:25 GMT
- Title: A Hybrid Approach to Full-Scale Reconstruction of Renal Arterial Network
- Authors: Peidi Xu, Niels-Henrik Holstein-Rathlou, Stinne Byrholdt S{\o}gaard,
Carsten Gundlach, Charlotte Mehlin S{\o}rensen, Kenny Erleben, Olga
Sosnovtseva, Sune Darkner
- Abstract summary: We propose a hybrid framework to build subject-specific models of the renal vascular network.
We use semi-automated segmentation of large arteries and estimation of cortex area from a micro-CT scan as a starting point.
Our results show a statistical correspondence between the reconstructed data and existing anatomical data obtained from a rat kidney.
- Score: 5.953404851562665
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The renal vasculature, acting as a resource distribution network, plays an
important role in both the physiology and pathophysiology of the kidney.
However, no imaging techniques allow an assessment of the structure and
function of the renal vasculature due to limited spatial and temporal
resolution. To develop realistic computer simulations of renal function, and to
develop new image-based diagnostic methods based on artificial intelligence, it
is necessary to have a realistic full-scale model of the renal vasculature. We
propose a hybrid framework to build subject-specific models of the renal
vascular network by using semi-automated segmentation of large arteries and
estimation of cortex area from a micro-CT scan as a starting point, and by
adopting the Global Constructive Optimization algorithm for generating smaller
vessels. Our results show a statistical correspondence between the
reconstructed data and existing anatomical data obtained from a rat kidney with
respect to morphometric and hemodynamic parameters.
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