Susceptibility artifacts induced by crowns of different materials with prepared teeth and titanium implants in magnetic resonance imaging

This study aimed to investigate the artifacts induced by crowns composed of different materials with prepared teeth and titanium implants. Resin, metal-ceramic, ceramic and zirconia crowns were fabricated and placed onto the prepared teeth on a human cadaver head or titanium implants with prosthesis abutments on a dry human mandible. The samples were scanned on a 1.5 T MRI apparatus, and artifact areas were defined as the signal intensity and signal loss adjacent to the prosthesis and measured by a threshold tool with ImageJ2x. Data were analyzed using SPSS 22.0. Resin, ceramic, zirconia, and precious metal-ceramic crowns barely produced artifacts on the cadaver skull (p > 0.999). By contrast, pure Ti and nonprecious metal-ceramic crowns created significant artifacts (p < 0.001). The average artifacts reduction of double Au-Pt and Ag-Pd metal-ceramic crowns combined with titanium implants and abutments was 79.49 mm2 (p < 0.001) and 74.17 mm2 (p < 0.001) respectively, while artifact areas were increased in double Co-Cr and Ni–Cr metal-ceramic crowns by 150.10 mm2 (p < 0.001) and 175.50 mm2 (p < 0.001) respectively. Zirconia, ceramic and precious metal-ceramic crowns induce less MRI artifacts after tooth preparation while precious metal-ceramic crowns alleviate artifacts in combination with titanium implants.

Completion of Metal-Damaged Traces Based on Deep Learning in Sinogram Domain for Metal Artifacts Reduction in CT Images

In computed tomography (CT) images, the presence of metal artifacts leads to contaminated object structures. Theoretically, eliminating metal artifacts in the sinogram domain can correct projection deviation and provide reconstructed images that are more real. Contemporary methods that use deep networks for completing metal-damaged sinogram data are limited to discontinuity at the boundaries of traces, which, however, lead to secondary artifacts. This study modifies the traditional U-net and adds two sinogram feature losses of projection images—namely, continuity and consistency of projection data at each angle, improving the accuracy of the complemented sinogram data. Masking the metal traces also ensures the stability and reliability of the unaffected data during metal artifacts reduction. The projection and reconstruction results and various evaluation metrics reveal that the proposed method can accurately repair missing data and reduce metal artifacts in reconstructed CT images.

Performance Comparison Study of Several Interpolation Methods on Streak Metal Artifacts Reduction of CT Images

In the course of generating the CT images, the streak metal artifacts emerge from the reconstructed images, often degraded the quality of the images and blur the fringe information around the metal implant. Although a number of attempts had been reported, among them, our proposed interpolation-based method is the simplest and most efficient approaches. In this paper, three interpolation approaches are compared with subjective and objective criterion based on both simulation and clinical cases. Our results have shown an improvement from the original images. As for the comparison with NRMSD and MAD. For the execution time, the L-MAR possesses the shortest time with S-MAR time being the slowest among the interpolation-based methods. For NRMSD and MAD, the digits from small to large are P-MAR, S-MAR, L-MAR and original. This shows that among interpolation-based methods the image corrected by P-MAR approach is the closest to the ideal image, followed by S-MAR correction, L-MAR correction, and the gap between the original image and the ideal image is the largest.

Sensitivity and Adjustment Model of Electrocardiographic Signal Distortion Based on the Electrodes’ Location and Motion Artifacts Reduction for Wearable Monitoring Applications

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by WHO. Some wearables devices have been developed to monitor the ECG in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an ECG signal waveform comparison when the location of electrodes is changed, to find a electrodes&rsquo; location that reduces distortion of interest signals. In addition, effect of motion artifacts and electrodes&rsquo; location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain ECG signals, the result was compared with a computational model of the heart behavior through the EA ECG, DTW and SNR methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the ECG signal from the patient&rsquo;s torso or back without a significant difference, and the electrodes position can be moved 6cm at most from the suggested location by the Einthoven triangle in Mason-Likar&rsquo;s method.

Real-Time Artifacts Reduction during TMS-EEG Co-Registration: A Comprehensive Review on Technologies and Procedures

Transcranial magnetic stimulation (TMS) excites neurons in the cortex, and neural activity can be simultaneously recorded using electroencephalography (EEG). However, TMS-evoked EEG potentials (TEPs) do not only reflect transcranial neural stimulation as they can be contaminated by artifacts. Over the last two decades, significant developments in EEG amplifiers, TMS-compatible technology, customized hardware and open source software have enabled researchers to develop approaches which can substantially reduce TMS-induced artifacts. In TMS-EEG experiments, various physiological and external occurrences have been identified and attempts have been made to minimize or remove them using online techniques. Despite these advances, technological issues and methodological constraints prevent straightforward recordings of early TEPs components. To the best of our knowledge, there is no review on both TMS-EEG artifacts and EEG technologies in the literature to-date. Our survey aims to provide an overview of research studies in this field over the last 40 years. We review TMS-EEG artifacts, their sources and their waveforms and present the state-of-the-art in EEG technologies and front-end characteristics. We also propose a synchronization toolbox for TMS-EEG laboratories. We then review subject preparation frameworks and online artifacts reduction maneuvers for improving data acquisition and conclude by outlining open challenges and future research directions in the field.