An ITK Implementation of a Diffusion Tensor Images Resampling Filter
Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3189
New: Prefer using the following doi: https://doi.org/10.54294/brogba
This paper describes the implementation of a resampling ﬁlter for Diffusion Tensor Images (DTI) in the Insight ToolKit (ITK). ITK already contains a ﬁlter for resampling scalar and vector images as well as several transformation and interpolation classes. However, due to the directional nature of DT images, using the existing classes would result in losing the structural information of the image. We developed a new resampling ﬁlter, speciﬁc to DTI, that preserves the structure by applying a rotation directly on the tensors while performing the transformation of the image. New transformation and interpolator classes have also been implemented to handle tensors correctly. The new transformation classes are based on algorithms described by D.C. Alexander et al. Finally, three ﬁlters have been written to correct symmetric semi-deﬁnite matrices that would no longer be positive after the resampling process and project them into the tensors’ space. In addition, a software based on the new classes has been developed and is provided with this article.