title: Quantitative analysis of vascular parameters for micro-CT imaging of vascular networks with multi-resolution.
abstract: Previous studies showed that all the vascular parameters from both the morphological and topological parameters were affected with the altering of imaging resolutions. However, neither the sensitivity analysis of the vascular parameters at multiple resolutions nor the distinguishability estimation of vascular parameters from different data groups has been discussed. In this paper, we proposed a quantitative analysis method of vascular parameters for vascular networks of multi-resolution, by analyzing the sensitivity of vascular parameters at multiple resolutions and estimating the distinguishability of vascular parameters from different data groups. Combining the sensitivity and distinguishability, we designed a hybrid formulation to estimate the integrated performance of vascular parameters in a multi-resolution framework. Among the vascular parameters, degree of anisotropy and junction degree were two insensitive parameters that were nearly irrelevant with resolution degradation; vascular area, connectivity density, vascular length, vascular junction and segment number were five parameters that could better distinguish the vascular networks from different groups and abide by the ground truth. Vascular area, connectivity density, vascular length and segment number not only were insensitive to multi-resolution but could also better distinguish vascular networks from different groups, which provided guidance for the quantification of the vascular networks in multi-resolution frameworks.
authors.affiliation: Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China.
authors.forename: Fengjun
authors.initials: F
authors.lastname: Zhao
authors.affiliation: Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China. jiminliang@gmail.com.
authors.forename: Jimin
authors.initials: J
authors.lastname: Liang
authors.affiliation: Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China.
authors.forename: Xueli
authors.initials: X
authors.lastname: Chen
authors.affiliation: Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China.
authors.forename: Junting
authors.initials: J
authors.lastname: Liu
authors.affiliation: Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China.
authors.forename: Dongmei
authors.initials: D
authors.lastname: Chen
authors.affiliation: Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China.
authors.forename: Xiang
authors.initials: X
authors.lastname: Yang
authors.affiliation: Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China.|Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Tian
mesh_terms: D000792:Angiography; D000818:Animals; D001808:Blood Vessels / Q000033:anatomy & histology*; D003198:Computer Simulation; D021621:Imaging, Three-Dimensional; D051381:Rats; D015203:Reproducibility of Results; D055114:X-Ray Microtomography / Q000379:methods*
keywords: Micro-computed tomography; Multi-resolution; Quantitative analysis; Vascular networks