Fig. 2: Representative images and quantitative results of the deep-learning resting-state cerebrovascular reactivity (DLRS CVR) and bolus arrival time (DLRS BAT).
From: Deep-learning-enabled brain hemodynamic mapping using resting-state fMRI
a–c Representative images from a healthy volunteer (a), Moyamoya disease patient (b), brain tumor patient (c). From left to right, the images are T1-weighted anatomic images, raw BOLD images, hypercapnic (HC) CVR, DLRS CVR, global-regression resting-state (GRRS) CVR, HC BAT, DLRS BAT and GRRS BAT. d–g The boxplots display the similarity between resting-state CVR maps and ground-truth HC CVR maps. Two types of resting-state CVR maps were studied: the proposed DLRS CVR and an existing GRRS CVR. Four similarity indices were studied, including Pearson cross-correlation (d), structure similarity index metric (SSIM) (e), peak signal-to-noise ratio (PSNR) (f), root-mean-square error (RMSE) (g). The line within the boxplots represents the median, the box represents the interquartile range (IQR), and the whiskers are 1.5 times the IQR. h–k the boxplots display the similarity between resting-state BAT maps and ground-truth HC BAT maps.
