Enabling Anatomical Diffusion Parameter Maps[1, 7, 8]
Neuroimaging through dMRI traditionally grapples with imaging resolution against noise. Through a combination of denoising and Bayesian parameter estimation, it is possible to maximize the precision while minimizing bias to produce maps high fidelity quantitative maps.
Parameter maps of mean diffusivity (MD), fractional anisotropy (FA), directionally encoded color FA (cFA), and radial kurtosis (RK) are compared between standard and MICSI-DMRI parameter estimation.
MP-PCA was used to preprocess both of these datasets, therefore the artifacts of the standard approach are unrelated to noise. The white arrows on standard cFA show regions within the cerebrospinal fluid (CSF), which incorrectly show fibrous structure, as though this fluid contains dense white matter.
The white arrows on standard cFA show regions within the cerebrospinal fluid (CSF).
A. Axial section of the brainstem section at the level of the trigeminal nerve, clearly visualized at high resolution.
B. Axial section of the thalamus, showing various tracts and thalamic nuclei.
C. Axial section of the motor and somatosensory cortex, revealing green u-fibers connecting nearby cortical areas.
D. Axial section of the cerebral peduncle and substantia nigra.
E. Para-sagittal image of callosum - stria medullaris ventral to the fornix.
F. Coronal image through anterior left medial temporal lobe - alveus & fimbria (arrow) / stratum lacunosum of hippocampus proper.
Functional MRI (fMRI) has been one of the greatest success stories of neuroimaging and has transformed our understanding of the brain by allowing us to visualize and measure brain activity. However, its application in medical imaging faces challenges related to:
As an enabling technology for clinical functional MRI, MP-PCA is capable of boosting the signal-to-noise ratio (SNR) commensurate with the number of temporal frames in the fMRI time-series. The extra SNR provided by MP-PCA can be strategically utilized to mitigate issues stated above.
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