| [12] |
b-value (700-1000) |
FA |
Average FA decreases with increasing b-value. |
| [29] |
b-value (500-2500) |
FA, MD, AD, RD |
Small FA variation with varying b-value (variation depends on tissue type and age). MD, AD and RD decrease with increasing b-value. |
| [30] |
b-value |
FA, MD, AD, RD |
FA error due to PVE decreases with higher b-value. MD decreases with increasing b-value. In presence of PVE, FA decreases with higher b-values, while MD, AD and RD increase. |
| [31] |
b-value |
FA |
In regions with intermediate FA, high b-value (>3000) and low SNR produce FA underestimation and eigenvector shift. |
| [32] |
b-value |
FA, MD |
Simulated data (FA = 0.9). Correct FA estimation for b-values between 500 and 1500. FA underestimation for b-values over 3000. MD decreases with increasing b-values. |
| [33] |
b-value (160-800) |
FA |
Phantoms and real data. Increasing b-values reduces standard dev. of FA. |
| [34] |
Resolution |
FA |
Smaller voxel size increases FA. |
| [35] |
Resolution, gradient directions |
FA |
Smaller voxel size increases FA. A higher number of gradient directions decreases FA. |
| [36] |
Resolution |
MD |
MD does not change with voxel size. |
| [13] |
Gradient directions |
FA |
Simulated data. A higher number of gradient directions decreases estimated FA and its standard deviation. |
| [14] |
Gradient directions, SNR |
FA, MD |
A higher number of gradient directions decreases estimated FA and its standard deviation. Importance of a well-balanced gradient directions scheme. Higher SNR reduces standard deviation in FA and MD (simulated data). |
| [25] |
Gradient directions, SNR |
FA, MD |
A higher number of gradient directions increases estimated FA while reducing MD. Lower noise increases FA. |
| [37] |
Gradient directions |
FA, MD, RA |
20 gradient directions are enough for FA and MD estimation. 30 are needed for RA. |
| [10] |
SNR |
FA, MD |
Higher noise increases FA, while MD does not change. |
