Multi-resolution T1w Brain MRI simulated data
Description
This simulated data is based on the patient-specific brain phantoms that are generated by utilizing high resolution real subject 3D brain MRI data and performing automatic segmentations for all brain tissues. The brain MRI imaging dataset is obtained from the HCP healthy young adult sample. We selected two hundred unprocessed structural T1w brain MRI scans for phantom generation. The phantoms are created by applying the Philips proprietary automated complete brain segmentation tool on HR T1w structural MRI data. Tissue parameters including longitudinal relaxation time (T1), transverse relaxation time (T2) and proton density (PD) are assigned to each tissue in each phantom. These parameters are collected from literature and random samples are taken from the bounded Gaussian bell distribution of given mean and standard deviation for each tissue relaxation times. MRI data is simulated for T1w brain MRI using our Matlab-based simulation framework. Using the phantoms as input, MRI data is simulated at two different resolutions for voxel aligned paired data, i.e. HR and LR of 0.7𝑚𝑚 and 1𝑚𝑚 respectively in both phase encoding directions. A fixed slice thickness of 1𝑚𝑚 (axial) is used for both HR and LR data. To have HR-LR paired data aligned on voxel level, zero padding in k-space is performed for LR data, i.e. the size of the LR k-space is made equal to the size of the HR k-space and then Fourier reconstructions are performed. The resulting size of simulated data is 320x320x179 for both HR and LR MRI. Ernst angle solution for a gradient echo (GRE) sequence with fixed sequence parameters of TR 18𝑚𝑠, TE 10𝑚𝑠 and FA of 30◦ is used to simulate all pairs of data. The T1w intensities are computed for each voxel. A complex Gaussian noise (standard deviation 0.4) is generated, which is derived from the simulated WM (intensity range 0−4095) in the MRI volume. The generated complex Gaussian noise is added to the real and imaginary part of the k-space data before FFT reconstructions. It is essential to emphasize that our simulation process intentionally did not introduce any MR imaging artifacts. The folder structure of the paired HR-LR database is as follow: 1. HR (contains 200 T1w brain MRI simulated images in Nifti format at in-plane resolution of 0.7x0.7𝑚𝑚 with slice thickness of 1𝑚𝑚) 2. LR (contains 200 T1w brain MRI simulated images in Nifti format at in-plane resolution of 1x1𝑚𝑚 with slice thickness of 1𝑚𝑚) 3. Figures (the resulting figures of brain MRI SR in png format for the associated article "Effective deep-learning brain MRI super resolution using simulated training data")