Abstract
Hybrid X-ray and magnetic resonance (MR) imaging promises large potential in interventional medical imaging applications due to the broad variety of contrast of MRI combined with fast imaging of X-ray-based modalities. To fully utilize the potential of the vast amount of existing image enhancement techniques, the corresponding information from both modalities must be present in the same domain. For image-guided interventional procedures, X-ray fluoroscopy has proven to be the modality of choice. Synthesizing one modality from another in this case is an ill-posed problem due to ambiguous signal and overlapping structures in projective geometry. To take on these challenges, we present a learning-based solution to MR to X-ray projection-to-projection translation. We propose an image generator network that focuses on high representation capacity in higher resolution layers to allow for accurate synthesis of fine details in the projection images. Additionally, a weighting scheme in the loss computation that favors high-frequency structures is proposed to focus on the important details and contours in projection imaging. The proposed extensions prove valuable in generating X-ray projection images with natural appearance. Our approach achieves a deviation from the ground truth of only 6% and structural similarity measure of 0.913 ± 0.005. In particular the high frequency weighting assists in generating projection images with sharp appearance and reduces erroneously synthesized fine details.
Highlights
Medical imaging offers various possibilities to visualize soft and hard tissue, physiological processes, and many more
The synthesis of X-ray-like projection images for further processing based on the acquired magnetic resonance imaging (MRI) signal is, an inherently ill-posed problem
While magnetic resonance (MR) projection imaging allows for continuous intraoperative use due to much faster acquisition times compared to volumetric MRI scans, the structural information diminishes in the projection image by integrating the intensity or attenuation values on the detector
Summary
Medical imaging offers various possibilities to visualize soft and hard tissue, physiological processes, and many more. The reasons for this are the high spatial and temporal resolution, which make the handling of interventional devices much easier By complementing these advantages with better soft tissue contrast provided by MRI, the gain from the simultaneous acquisition of soft and dense tissue information through hybrid imaging would offer great opportunities. While MR projection imaging allows for continuous intraoperative use due to much faster acquisition times compared to volumetric MRI scans, the structural information diminishes in the projection image by integrating the intensity or attenuation values on the detector. This corresponds to a linear combination of multiple slice images with unknown path length which further increases the difficulty of the synthesis task. Enabled by the progress in fast MR projection acquisition, we investigate a solution for generating X-ray projections from corresponding MRI views by projection-to-projection translation
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