RT Journal Article
SR Electronic
T1 Intracranial Vessel Segmentation in 3D High-Resolution T1 Black-Blood MRI
JF American Journal of Neuroradiology
JO Am. J. Neuroradiol.
FD American Society of Neuroradiology
SP 1719
OP 1721
DO 10.3174/ajnr.A7700
VO 43
IS 12
A1 S. Elsheikh
A1 H. Urbach
A1 M. Reisert
YR 2022
UL http://www.ajnr.org/content/43/12/1719.abstract
AB SUMMARY: We demonstrate the feasibility of intracranial vascular segmentation based on the hypointense signal in non-contrast-enhanced black-blood MR imaging using convolutional neural networks. We selected 37 cases. Qualitatively, we observed no degradation due to stent artifacts, a comparable recognition of an aneurysm recurrence with TOF-MRA, and consistent success in the differentiation of intracranial arteries and veins. False-positive and false-negative results were observed. Quantitatively, our model achieved a promising Dice similarity coefficient of 0.72.BBMRIblack-blood compressed-sensing MRICNNconvolutional neural networksDSCDice similarity coefficient