Anatomical connectivity mapping: A new tool to assess brain disconnection in Alzheimer's disease

Track density imaging (TDI): Validation of super resolution property

“…On the other hand, as discussed in our earlier work , there may also be a quantitative role for the superresolution TDI technique, provided future studies show the method to have good quantitative reproducibility. In fact, recent work (Bozzali et al, 2011) has used an approach that has similarities to the TDI method (albeit without involving super-resolution), and demonstrated its potential role in voxel-based analysis.…”

Quantification of voxel-wise total fibre density: Investigating the problems associated with track-count mapping

“…Despite the well-known limitations with interpretation of track counts (Jones et al, 2013), there has been great interest in the use of streamlines density as a surrogate measure of local axonal density. Indeed, TDI and other related track-count mapping methods (Bozzali et al, 2011;Stadlbauer et al, 2010) have been applied quantitatively in a number of brain disorders. For example, TDI has been quantitatively applied to study patients with glioblastoma multiforme (Barajas et al, 2013), as well as to identify image abnormalities in Parkinson's disease (Ziegler et al, 2014).…”

“…For example, TDI has been quantitatively applied to study patients with glioblastoma multiforme (Barajas et al, 2013), as well as to identify image abnormalities in Parkinson's disease (Ziegler et al, 2014). Similarly, anatomical connectivity mapping (Bozzali et al, 2011) and fibre density mapping (Stadlbauer et al, 2010) are two techniques that are essentially similar to TDI at native resolution (i.e. without super-resolution; Calamante et al, 2011), and have been used quantitatively in numerous applications; these include to investigate Alzheimer's disease (Bozzali et al, 2013a(Bozzali et al, , 2011, multiple sclerosis (Bozzali et al, 2013b;Lyksborg et al, 2014), gliomas (Stadlbauer et al, 2012(Stadlbauer et al, , 2011(Stadlbauer et al, , 2010, and age-related brain changes (Stadlbauer et al, 2012).…”

Registration of FA and T1-Weighted MRI Data of Healthy Human Brain Based on Template Matching and Normalized Cross-Correlation

“…Initial spatial alignment of FA and T1 data is usually based on a global rigid or affine geometric transforms [2,11,12], followed by a 3D deformable registration method. Li and Verma [13] proposed multimodal feature based image registration using Gabor wavelet transform to create an image collection suitable for multichannel image analysis.…”