Neural attenuation fields for metal artifact reduction in dental CT

Jooho Lee; Junhyun Ahn; Jongduk Baek

doi:10.1117/12.2689652

1 April 2024 Neural attenuation fields for metal artifact reduction in dental CT

Jooho Lee, Junhyun Ahn, Jongduk Baek

Proceedings Volume 12925, Medical Imaging 2024: Physics of Medical Imaging; 1292514 (2024) https://doi.org/10.1117/12.2689652
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Abstract

Metal Artifact Reduction (MAR) is one of the notorious problems in dental CT imaging. The presence of metallic implants often introduces severe metal artifacts in the reconstructed CT images, which obstruct the visualization of dental structures. This highly ill-posed problem has been addressed with the rise of artificial intelligence in respect to deep learning. However, majority of the approaches rely on the supervision of large paired dataset, which is often infeasible in the clinical practice. In this work, we present NeMAR, a Neural fields-based Metal Artifact Reduction method for dental CT. NeMAR leverages coordinate-based neural representation along with two key components: the masked loss and the regularization loss. These elements synergistically empower the neural fields to generate metal-artifact-reduced CT image with high fidelity. Notably, NeMAR requires only the original metal-artifact-corrupted image as an input, thus eliminating the need for extensive paired data. The validation using simulated dental CT datasets demonstrates the effectiveness of NeMAR in accurately recovering the shape of dental structures. In essence, NeMAR presents a promising data-free approach to enhance dental CT imaging.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jooho Lee, Junhyun Ahn, and Jongduk Baek "Neural attenuation fields for metal artifact reduction in dental CT", Proc. SPIE 12925, Medical Imaging 2024: Physics of Medical Imaging, 1292514 (1 April 2024); https://doi.org/10.1117/12.2689652

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