A fast FFT based algorithm for spatial misalignment correction in along-tract group analysis

Abstract

While it is acknowledged that diffusion MRI datasets should be corrected for artifacts in population studies, the same is also recommended for fiber bundle group analyses. As shown previously, along-tract based statistics offer a more realistic estimation than using a single averaged value from the entire studied fiber bundle. There have been previously proposed bundle-based registration algorithms, but most statistical analysis are done at the single tract level, as for example by extracting the mean representative pathway. In this context, the mean fiber may not be optimally aligned between various subjects as opposed to the bundles themselves, which may lead to an increased bias in the subsequent statistical analysis. To alleviate this caveat, we propose a fast and straightforward 1D rigid registration algorithm for metrics extracted along tracts based on the fast Fourier transform (FFT) and the cross-correlation theorem. The algorithm works directly in the metric space by considering the extracted values as a 1D signal, thus making it perfectly suited for usage in population studies using any metric of interest.