The evaluation of a population based diffusion tensor image atlas using a ground truth method

Voxel based morphometry (VBM) is increasingly being used to detect diffusion tensor (DT) image abnormalities in patients for different pathologies. An important requisite for these VBM studies is the use of a high-dimensional, non-rigid coregistration technique, which is able to align both the spatial and the orientational information. Recent studies furthermore indicate that high-dimensional DT information should be included during coregistration for an optimal alignment. In this context, a population based DTI atlas is created that preserves the orientational DT information robustly and contains a minimal bias towards any specific individual data set. Methods: A ground truth evaluation method is developed using a single subject DT image that is deformed with 20 deformation fields. Thereafter, an atlas is constructed based on these 20 resulting images. Thereby, the non-rigid coregistration algorithm is based on a viscous fluid model and on mutual information. The fractional anisotropy (FA) maps as well as the DT elements are used as DT image information during the coregistration algorithm, in order to minimize the orientational alignment inaccuracies. Results: The population based DT atlas is compared with the around truth image using accuracy and precision measures of spatial and orientational dependent metrics. Results indicate that the population based atlas preserves the orientational information in a robust way. Conclusion: A subject independent population based DT atlas is constructed and evaluated with a ground truth method. This atlas contains all available orientational information and can be used in future VBM studies as a reference system.