Report
Spatially Regularized Super-Resolved Constrained Spherical Deconvolution (SR$^2$-CSD) of Diffusion MRI Data
| العنوان: | Spatially Regularized Super-Resolved Constrained Spherical Deconvolution (SR$^2$-CSD) of Diffusion MRI Data |
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| المؤلفون: | Taskin, Ekin, Haro, Juan Luis Villarreal, Girard, Gabriel, Rafael-Patiño, Jonathan, Garyfallidis, Eleftherios, Thiran, Jean-Philippe, Canales-Rodríguez, Erick Jorge |
| سنة النشر: | 2024 |
| المجموعة: | Physics (Other) |
| مصطلحات موضوعية: | Physics - Medical Physics, Electrical Engineering and Systems Science - Image and Video Processing |
| الوصف: | Constrained Spherical Deconvolution (CSD) is crucial for estimating white matter fiber orientations using diffusion MRI data. A relevant parameter in CSD is the maximum order $l_{max}$ used in the spherical harmonics series, influencing the angular resolution of the Fiber Orientation Distributions (FODs). Lower $l_{max}$ values produce smoother and more stable estimates, but result in reduced angular resolution. Conversely, higher $l_{max}$ values, as employed in the Super-Resolved CSD variant, are essential for resolving narrow inter-fiber angles but lead to spurious lobes due to increased noise sensitivity. To address this issue, we propose a novel Spatially Regularized Super-Resolved CSD (SR$^2$-CSD) approach, incorporating spatial priors into the CSD framework. This method leverages spatial information among adjacent voxels, enhancing the stability and noise robustness of FOD estimations. SR$^2$-CSD facilitates the practical use of Super-Resolved CSD by including a J-invariant auto-calibrated total variation FOD denoiser. We evaluated the performance of SR$^2$-CSD against standard CSD and Super-Resolved CSD using phantom numerical data and various real brain datasets, including a test-retest sample of six subjects scanned twice. In phantom data, SR$^2$-CSD outperformed both CSD and Super-Resolved CSD, reducing the angular error (AE) by approximately half and the peak number error (PNE) by a factor of three across all noise levels considered. In real data, SR$^2$-CSD produced more continuous FOD estimates with higher spatial-angular coherency. In the test-retest sample, SR$^2$-CSD consistently yielded more reproducible estimates, with reduced AE, PNE, mean squared error, and increased angular correlation coefficient between the FODs estimated from the two scans for each subject. Comment: 16 pages, 5 figures |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2408.12921 |
| رقم الانضمام: | edsarx.2408.12921 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |