## 3 Results
### Effect of Intensity Processing Procedures
#### 3.2.1 Intensity Inhomogeneity Correction  
N3 intensity homogeneity correction had a notable effect on the variance of the pipelines into which it was incorporated. While N3 offered virtually no improvement in the mean DSC of optiBET in T1-MPRAGE images, it did reduce the standard deviation by roughly half, decreasing it from 0.0455 to 0.0258 for N3 iter = 1 and 0.0265 for N3 iter = 4. This effect is also represented in Figure 2, which shows that pipelines with N3 have higher DSC scores in the bottom 10 th percentile of DSC scores relative to control pipelines and other IP procedures for optiBET and several BET extraction configurations. Specifically, this effect is observed in the BET, BET! R, BET! B, BET! B, f0.2, g0.3, and BET! B, f0.1 extraction configurations (Figure 2g-k). For these configurations, N3 iter = 1 showed a robust decrease  
Figure 5: The impact of intensity processing procedures on brain extraction performance as the percent difference in mean DSC for T2-FLAIR MRIs. The bars in the subplots represent the variation in mean DSC associated with each IP procedure/extraction configuration relative to the mean DSC of the control pipeline. Subplots (**a**) through (**k**) show the effect of the IP Procedures on the accuracy of the following configurations: BET (**a**), BET! B (**b**), BET! B, f0.1 (**c**), BET! B, f0.2, g0.3 (**d**), BET! R (**e**), BET! R.2 (**f**), BET! f0.2, g0.3 (**g**), BET! f0.8 (**h**), BET! g-0.3 (**i**), BET! g0.3 (**j**), and optiBET (**k**). Error bars indicate the standard error. Bars deflecting upward indicate an increase in mean DSC, and bars deflecting downward indicate a reduction in DSC. in the standard deviation relative to the control pipeline, while N3 iter = 4 showed a smaller reduction in the standard deviation (Table 3). However, N3 does not have this effect in the five lowest-performing BET configurations in Figure 2.  
In addition to the differences in variance shown in Table 3 and Figure 2, pipelines incorporating N3 homogeneity correction had the largest effect on the mean DSC from their respective control pipelines for T1-MPRAGE MRIs. As Figure 4 shows, N3 iter = 1 and N3 iter = 4 both significantly increased DSC relative to the control pipeline across the default BET, BET 1 R, and BET 1 B configurations (\(p<0.001\)). Notably, N3 iter = 4 had a significantly larger positive effect than N3 iter = 1 on default BET (\(p<0.02\)) and BET 1 R (\(p<0.001\)). For BET 1 g(-0.3), both N3 iterations showed significant improvements, with \(p\)-values \(<0.02\) for N3 iter = 1 and \(p<0.05\) for N3 iter = 4. Similarly, both iterations increased the DSC for BET 1 B,f0.1, with N3 iter = 1 outperforming N3 iter = 4 (\(p<0.01\)). In the case of BET 1 B,f0.2,g0.3, N3 iter = 1 had a more substantial positive effect compared to N3 iter = 4 (\(p<0.05\)). Conversely, for optiBET, N3 iter = 1 exhibited a significant positive effect, whereas N3 iter = 4 had a slight negative impact (\(p<0.001\)). Similarly, for BET 1 f0.2,g0.3, and BET 1 f0.8, N3 iter = 4 demonstrated a significant decrease in DSC relative to the control pipelines and showed a larger decrease in DSC compared to N3 iter = 1 (\(p<0.001\) for BET 1 f0.2 and BET 1 f0.2,g0.3; \(p<0.001\) for BET 1 f0.8). Lastly, for the BET 1 g0.3 configuration, N3 iter = 1 had a significant negative effect, and so did N3 iter = 4 (\(p<0.001\)), with N3 iter = 4 having a significantly larger negative effect than N3 iter = 1 (\(p<0.001\)) (Figure 4). For T2-FLAIR images, N3 shows a pattern similar to but distinct from its effects on T1-MPRAGE images (represented in Figure 5). The decreasing effect of N3 on the standard deviation is similarly observed with T2-FLAIR images (Figure 5), with N3 reducing the standard deviations of BET 1 B, BET 1 B,f0.1, BET 1 B,f0.2,g0.3, and optiBET by over 50 percent in some cases. However, opposite to the results for T1-MPRAGE images, reductions in the SDs of these configurations were larger with N3 iter = 4 than with N3 iter = 1.