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It is important to recognize that there are fundamental limits on the ability of diffusion tractography to accurately estimate anatomical connectivity15,16, which may contribute to the considerable number of partial correlations with no measured structural connection according to diffusion.
In diseased tissue with decreased ability of diffusion, the activated 1H protons obtain decreased mobility and thus remain at almost the same place.
Recent studies highlighted the ability of diffusion weighted imaging (DWI) to differentiate cholesteatoma from other inflammatory diseases of the middle ear [ 6].
Nowadays, a huge number of papers have documented the ability of diffusion magnetic resonance imaging (D-MRI) to highlight normal and pathological conditions in a variety of cerebral, abdominal, and cardiovascular applications.
Although it is known that size criteria lack the desired accuracy for characterizing lymph nodes, our results showed that for the purpose of pre-treatment staging, the ability of diffusion MRI for detection of lymph node involvement based on size criteria alone (i.e., node larger than 10 mm in the "greatest" transverse diameter according to Cheson et al).
Since the early publications by Le Bihan [ 1] and Basser [ 2– 4] a great number of papers have documented the ability of diffusion magnetic resonance imaging (D-MRI) to define and discriminate normal and pathological conditions in a variety of cerebral [ 5, 6], abdominal [ 7– 10] and cardiovascular applications [ 11, 12].
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The objective of this review is to assess the ability of diffusion-weighted magnetic resonance imaging (MRI) to predict the short-term risk of stroke.
Some studies additionally investigated the ability of diffusion-weighted imaging (DWI) for assessing pCR after NAC.
The ability of hindered diffusion models previously presented in the literature to fit the experimental data is examined.
Such improvement is associated with the prominent appearance of spinel-like regions transferred from the original Li2MnO3 component in which Ru facilitates the phase transformation via enhancing the ability of Li diffusion in both Li2MnO3 and LiNi1/3Co1/3Mn1/3O2 components.
It is concluded that the ability of a diffusion kernel to capture the total genetic variance is not better than that of a Gaussian kernel, at least for these data.
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