In QBI, the numerical estimation includes re-sample diffusion at the radial directions before Funk-Randon transforms or using spherical decomposition to estimate spherical harmonics for calculating the transform before converting it back to the ODF. In DSI, the numerical estimation includes a Fourier transform, followed by a filter to remove noise and a radial integration with numerical interpolation. If you are using DSI or QBI reconstruction, consider placing them with GQI for the following reasons: DSI and QBI offer only a numerical estimation of the diffusion ODF while GQI offers a direct analytical relation for the diffusion ODF (termed SDF here). The downside of model-free methods is that they often need more diffusion samplings, at least 60 to get a more robust estimation (In comparison, DTI only needs 6 samplings in addition to b0). The calculation does not require complicated optimization or fitting and thus is less affected by outliers in comparison with the model-based methods. It does not have the overfitting problem in the model-based method. They do not assume a particular diffusion structure, and there is no risk for violation of the model. The advantage of model-free methods is that they are not limited by a model.
#Qspace vs k space free
This relation allows GQI to directly compute SDF and thus be free from the error in the numerical estimation. SDF is the density of diffusing water in a different direction and is a kind of diffusion ODF. GQI provides an analytical relation between diffusion signals and the spin distribution function (SDF) and can be applied to any diffusion sampling scheme. HARDI acquisition, single b-value, multiple directions). The calculation requires a shell-like diffusion sampling scheme (i.e. QBI uses either Funk-Randon transform or spherical harmonics to calculate the ODF. The Fourier transform requires a specific grid diffusion sampling scheme (multiple b-values multiple directions). DSI uses Fourier transformation and numerical integration to calculate the orientation distribution function (ODF, which is the empirical distribution of water diffusion at different orientations) of water diffusion. The methods include diffusion spectrum imaging (DSI), q-ball imaging (QBI), and generalized q-sampling imaging (GQI). Model-free methods estimate the empirical distribution of water diffusion, and there is no assumption on the distribution. For example, past studies have used a bi-exponential model to fit intra-cellular and extra-cellular diffusion, but it turned out that they failed to reveal such biophysics. A complicated model may also have an overfitting problem. However, the results of model-based methods are limited by the model, and it is common that the diffusion pattern does not follow the assumption. The strength of model-based methods, similar to the parametric methods in statistics, is that they only require a few samples to get the whole distribution. The ball-and-sticks model is a kind of multiple tensor model, whereas the ball is the isotropic Gaussian, and the sticks is a purely anisotropic Gaussian. For example, DTI assumes that the velocity of water diffusion follows a 3D Gaussian distribution, and the tensor calculated is exactly the covariance matrix of the Gaussian. Model-based methods assume a particular diffusion distribution pattern/function, and the parameters are calculated by fitting diffusion signals with the model. Model-based methods Model-based methods include DTI, ball-and-sticks model, NODDI as well as a more complicated model like CHARM and AxCaliber. Both model-based and model-free methods have their strength and weakness: Gaussian) to obtain inference, whereas non-parametric or model-free approaches assume no underlying distribution/model and obtain inference using empirical distribution. The parametric or model-based approaches assume a known distribution/model (e.g. This categorization is similar to the classification of the parametric and non-parametric methods in statistics.
5 Optional: Reconstruction Using MATLAB.4.4 Q-Space Diffeomorphic Reconstruction (QSDR).4.2 Generalized Q-sampling Imaging (GQI).
4 Step T2b(1): Select a Reconstruction Method.
0 kommentar(er)
