Title
A Comparative Analysis Framework Of 3t And 7t Tof-Mra Based On Automated Cerebrovascular Segmentation
Abstract
Purpose: High field strength 3T and 7T Time-Of-Flight Magnetic Resonance Angiography (TOF- MRA) achieves better visualization of intracranial vessels, so it attracts much attention. However, quantitative comparison between 3T and 7T MRA is lacking in the aspects of image quality and the practical application of cerebrovascular diseases.Methods: In this paper, a quantitative framework of 3T and 7T TOF-MRA comparison is proposed, which contains two steps including the automated cerebrovascular segmentation and statistical analysis. Firstly, the whole vascular structures on both 3T and 7T TOF-MRA images are segmented automatically, especially those small blood vessels in 7T MRA. The skeleton extraction-based automatic seed point detection is implemented to ensure the segmented vascular structure complete and precise. Secondly, the statistical analysis of the differences between 3T and 7T MRA is carried out in the aspects of image quality and the characteristics of some important vessels. The objects of statistical analysis are achieved and analyzed automatically without needing the timeconsuming human beings? participation, therefore, it is efficient and objective.Results: The comparison experiments on seven pairs of 3T and 7T TOF MRA images validated that about image quality, the contrast-to-noise ratio of 7T MRA was about 4.53 ? 0.95 times as much as that of 3T MRA. About the cerebrovascular information, small vessels were more abundant in 7T MRA compared with 3T MRA (branches number: 462.0 ? 58.5 vs 393.1 ? 63.3).Conclusions: The proposed framework can segment the whole cerebrovascular structure automatically and compare TOF-MRA with different field strengths objectively and quantitatively. It is helpful for clinical cerebrovascular disease, especially cerebral small vessel diseases.
Year
DOI
Venue
2021
10.1016/j.compmedimag.2020.101830
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
Keywords
DocType
Volume
Cerebrovascular structure, Automatic method, Imaging comparison, Field strengths
Journal
89
ISSN
Citations 
PageRank 
0895-6111
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Jia Liu100.68
Fang Chen200.68
Xianyu Wang301.69
Xinran Zhang43812.02
Kaibao Sun500.34
Rong Xue621.20
Hongen Liao739070.91