A Motion Correction Strategy for Multi-Contrast based 3D parametric imaging: Application to Inhomogeneous Magnetization Transfer (ihMT)
Soustelle, L.; Lamy, J.; Le Troter, A.; Hertanu, A.; Guye, M.; Ranjeva, J.-P.; Varma, G.; Alsop, D. C.; Pelletier, J.; Girard, O.; Duhamel, G.
Show abstract
PurposeTo propose an efficient retrospective image-based method for motion correction of multi-contrast acquisitions with a low number of available images (MC-MoCo) and evaluate its use in 3D inhomogeneous Magnetization Transfer (ihMT) experiments in the human brain. MethodsA framework for motion correction, including image pre-processing enhancement and rigid registration to an iteratively improved target image, was developed. The proposed method was compared to Motion Correction with FMRIBs Linear Image Registration Tool (MCFLIRT) function in FSL over 13 subjects. Native (pre-correction) and residual (post-correction) motions were evaluated by means of markers positioned at well-defined anatomical regions over each image. ResultsBoth motion correction strategies significantly reduced inter-image misalignment, and the MC-MoCo method yielded significantly better results than MCFLIRT. ConclusionMC-MoCo is a high-performance method for motion correction of multi-contrast volumes as in 3D ihMT imaging.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Combining Navigator and Optical Prospective Motion Correction for High-Quality 500 μm Resolution Quantitative Multi-Parameter Mapping at 7T 97%
- QSM Reconstruction Challenge 2.0: a realistic in silico head phantom for MRI data simulation and evaluation of susceptibility mapping procedures 97%
- Multi-echo Quantitative Susceptibility Mapping: How to Combine Echoes for Accuracy and Precision at 3 T 96%
Similar papers in this journal
- Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity 97%
- Multi-parametric quantitative spinal cord MRI with unified signal readout and image denoising 96%
- Increased Sensitivity and Signal-to-Noise Ratio in Diffusion-Weighted MRI using Multi-Echo Acquisitions 96%
Similar papers in this journal
- Fluid and White Matter Suppression Contrasts MRI Improves Deep Learning Detection of Multiple Sclerosis Cortical Lesions 96%
- TAPAS: A Thresholding Approach for Probability Map Automatic Segmentation in Multiple Sclerosis 96%
- Fully Automated Detection of Paramagnetic Rims in Multiple Sclerosis Lesions on 3T Susceptibility-Based MR Imaging 95%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.