DrDisco: Deep Registration for Distortion Correction of Diffusion MRI with single phase-encoding
| Autor: | Bian, Zhangxing, Shao, Muhan, Carass, Aaron, Prince, Jerry L. |
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| Rok vydání: | 2023 |
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| Druh dokumentu: | Working Paper |
| Popis: | Diffusion-weighted magnetic resonance imaging (DW-MRI) is a non-invasive way of imaging white matter tracts in the human brain. DW-MRIs are usually acquired using echo-planar imaging (EPI) with high gradient fields, which could introduce severe geometric distortions that interfere with further analyses. Most tools for correcting distortion require two minimally weighted DW-MRI images (B0) acquired with different phase-encoding directions, and they can take hours to process per subject. Since a great amount of diffusion data are only acquired with a single phase-encoding direction, the application of existing approaches is limited. We propose a deep learning-based registration approach to correct distortion using only the B0 acquired from a single phase-encoding direction. Specifically, we register undistorted T1-weighted images and distorted B0 to remove the distortion through a deep learning model. We apply a differentiable mutual information loss during training to improve inter-modality alignment. Experiments on the Human Connectome Project dataset show the proposed method outperforms SyN and VoxelMorph on several metrics, and only takes a few seconds to process one subject. Comment: To appear in Medical Imaging: Image Processing 2023 |
| Databáze: | arXiv |
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