Abstract
The intensity-curvature term is the concept at the root foundation of this paper. The concept entails the multiplication between the value of the image pixel intensity and the value of the classic-curvature (CC(x, y)). The CC(x, y) is the sum of all of the second order partial derivatives of the model polynomial function fitted to the image pixel. The intensity-curvature term (ICT) before interpolation E0(x, y) is defined as the antiderivative of the product between the pixel intensity and the classic-curvature calculated at the origin of the pixel coordinate system (CC(0, 0)). The intensity-curvature term (ICT) after interpolation EIN(x, y) is defined as the antiderivative of the product between the signal re-sampled by the model polynomial function at the intra-pixel location (x, y) and the classic-curvature. The intensity-curvature functional (ICF) is defined as the ratio between E0(x, y) and EIN(x, y). When the ICF is almost equal to the numerical value of one (‘1’), E0(x, y) and EIN(x, y) are two additional domains (images) where to study the image from which they are calculated. The ICTs presented in this paper are able to highlight the human brain vessels detected with Magnetic Resonance Imaging (MRI), through a signal processing technique called inverse Fourier transformation procedure. The real and imaginary parts of the k-space of the ICT are subtracted from the real and imaginary parts of the k-space of the MRI signal. The resulting k-space is inverse Fourier transformed, and the human brain vessels are highlighted.Int. J. Appl. Sci. Biotechnol. Vol 5(3): 326-335
Highlights
The LiteratureTaking advantage of the magnetic susceptibility of deoxyhemoglobin, at ultra-high field (UHF) Magnetic Resonance Imaging (MRI) offers the possibility to image the vasculature of the human brain (Christoforidis et al, 1999)
It is due to acknowledge that the intensity-curvature functional (ICF) is similar to MRI high pass filtered signal and as such it is useful as an alternative high pass filter of the MRI signal (Ciulla et al, 2016)
The results show that the intensity-curvature term (ICT) have imaging capabilities that make them suitable to highlight the human brain vasculature imaged with MRI
Summary
Taking advantage of the magnetic susceptibility of deoxyhemoglobin, at ultra-high field (UHF) MRI offers the possibility to image the vasculature of the human brain (Christoforidis et al, 1999). The localization and the identification of the human brain vasculature is tight to changes in the susceptibility of the human brain tissues. The MRI technique called Susceptibility Weighted Imaging (SWI) which is based on gradient echo scans (T2* imaging) combined with unwrapped high-pass filtered phase images, provides the MRI images with contrast enhancement sufficient to image the vasculature, to enhance. Ciulla et al (2017) Int. J.
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