Table 1.
DTI data acquisition parameters for the different MRI scanners utilized in the current study.
Fig 1.
Schematic representation of the three pipelines utilized for brain DTI data processing.
The T1- and T2-weighted imaging processing subpipelines are common to all DTI processing pipelines. The blue, red, and purple arrows depict the 1st, 2nd, and 3rd DTI processing pipelines, respectively. T1 = T1-weighted image, T2 = T2-weighted image, b0 = b0 image.
Fig 2.
(A) FA, (B) MD, (C) AD, and (D) RD maps produced from the raw ground truth DWI data by the three DTI processing pipelines and directly from the ground truth data. First, second, and third columns correspond to the 1st, 2nd, and 3rd DTI processing pipeline, respectively. The fourth column corresponds to the maps obtained directly from the ground truth data. (E) The corresponding T1-weighted structural image and (F) full-brain segmentation of cerebral tissues (WM, GM, and CSF) are also provided. The images were not interpolated.
Fig 3.
FA maps produced by the three proposed DTI processing pipelines from the DWI datasets containing artefacts.
First, second, and third columns correspond to the 1st, 2nd, and 3rd DTI processing pipeline, respectively. First, second, third, and forth rows correspond to datasets LM-20, LM-40, SM-20, and SM-40, respectively. The corresponding T1-weighted structural image and full-brain segmentation of cerebral tissues are provided in panels e and f of Fig 2, respectively. The images were not interpolated.
Fig 4.
MD maps produced by the three proposed DTI processing pipelines from the DWI datasets containing artefacts.
First, second, and third columns correspond to the 1st, 2nd, and 3rd DTI processing pipeline, respectively. First, second, third, and forth rows correspond to datasets LM-20, LM-40, SM-20, and SM-40, respectively. The corresponding T1-weighted structural image and full-brain segmentation of cerebral tissues are provided in panels e and f of Fig 2, respectively. The images were not interpolated.
Fig 5.
Processing error associated with the pipelines for FA calculation in (A) WM and in (B) GM, and MD calculation in (C) WM and in (D) GM.
Fig 6.
Distribution of FA values in the WM region generated by the three pipelines after processing the ground-truth data.
Fig 7.
Distribution of the MD values in the WM region generated by the three pipelines after processing of the ground-truth data.
Fig 8.
Percentage error associated with each pipeline when processing data containing artefacts.
(A) shows FA in WM, (B) shows MD in WM region.
Fig 9.
FA measurements in NAWM from 20 ONDRI VCI subjects.
Fig 10.
MD measurements in NAWM from 20 ONDRI VCI subjects.
Fig 11.
Percentage error in calculation of FA in WM for the dataset LM-20 when using the gradient anisotropic diffusion (GAD) filter and Rician linear minimum mean square error (LMMSE) filter.
All pipelines produced lower percentage error with the GAD filter.
Fig 12.
FA maps for the dataset LM-20 obtained by different pipelines when using the gradient anisotropic diffusion (GAD) filter (first row) and Rician linear minimum mean square error (LMMSE) filter (second row).
First, second, and third columns correspond to the 1st, 2nd, and 3rd DTI processing pipeline, respectively. The images were not interpolated.