Reproducibility of Brain MRI Segmentation Algorithms: Empirical Comparison of Local MAP PSTAPLE, FreeSurfer, and FSL-FIRST.BACKGROUND AND PURPOSE
 Recently, the utility and accuracy of template library fusion algorithms, such as Local MAP PSTAPLE (PSTAPLE), have been demonstrated but there is little guidance regarding its reproducibility compared to single template-based algorithms such as FreeSurfer and FSL-FIRST.


 Eight repeated magnetic resonance imagings of 20 subjects were segmented using FreeSurfer, FSL-FIRST, and PSTAPLE.  PSTAPLE had the most reproducible volume measurements for hippocampus, putamen, thalamus, caudate, pallidum, amygdala, Accumbens area, and cortical regions.  PSTAPLE was the most accurate algorithm in terms of several metrics include Dice's coefficient.  The sample size estimates showed that a study utilizing PSTAPLE would require tens to hundreds less subjects than the other algorithms for detecting atrophy rates typically observed in brain disease.


 PSTAPLE is a useful tool for automatic human brain segmentation due to its precision and accuracy, which enable the detection of the size of the effect typically reported for neurological disorders with a substantially reduced sample size, in comparison to the other tools we assessed. 
PSTAPLE
Reproducibility of Brain MRI Segmentation Algorithms: Empirical Comparison of Local MAP PSTAPLE, FreeSurfer, and FSL-FIRST.BACKGROUND AND PURPOSE
 Recently, the utility and accuracy of template library fusion algorithms, such as Local MAP PSTAPLE (PSTAPLE), have been demonstrated but there is little guidance regarding its reproducibility compared to single template-based algorithms such as FreeSurfer and FSL-FIRST.


 Eight repeated magnetic resonance imagings of 20 subjects were segmented using FreeSurfer, FSL-FIRST, and PSTAPLE.  FreeSurfer was most reproducible for brainstem. 
FreeSurfer
Reproducibility of Brain MRI Segmentation Algorithms: Empirical Comparison of Local MAP PSTAPLE, FreeSurfer, and FSL-FIRST.BACKGROUND AND PURPOSE
 Recently, the utility and accuracy of template library fusion algorithms, such as Local MAP PSTAPLE (PSTAPLE), have been demonstrated but there is little guidance regarding its reproducibility compared to single template-based algorithms such as FreeSurfer and FSL-FIRST.


 Eight repeated magnetic resonance imagings of 20 subjects were segmented using FreeSurfer, FSL-FIRST, and PSTAPLE. 
FSL-FIRST