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3D Digital Modeling of Dental Casts from Their 3D CT Images with Scatter and Beam-Hardening Correction. | LitMetric

AI Article Synopsis

  • Dental 3D modeling is essential in digital dentistry for treatment planning and customizing implants and prostheses, moving away from traditional plaster casts due to issues with storage and accuracy.
  • A new method introduced in the study aims to reduce artifacts in CT scans, which enhances image quality significantly, including improvements in uniformity, contrast-to-noise ratio, and edge sharpness.
  • The method has shown a notable reduction in root mean square errors by 8.8-71.7% for various dental cast sizes, offering a promising solution for more accurate 3D models in dental applications.

Article Abstract

Dental 3D modeling plays a pivotal role in digital dentistry, offering precise tools for treatment planning, implant placement, and prosthesis customization. Traditional methods rely on physical plaster casts, which pose challenges in storage, accessibility, and accuracy, fueling interest in digitization using 3D computed tomography (CT) imaging. We introduce a method that can reduce both artifacts simultaneously. To validate the proposed method, we carried out CT scan experiments using plaster dental casts created from dental impressions. After the artifact correction, the CT image quality was greatly improved in terms of image uniformity, contrast-to-noise ratio (CNR), and edge sharpness. We examined the correction effects on the accuracy of the 3D models generated from the CT images. As referenced to the 3D models derived from the optical scan data, the root mean square (RMS) errors were reduced by 8.8~71.7% for three dental casts of different sizes and shapes. Our method offers a solution to challenges posed by artifacts in CT scanning of plaster dental casts, leading to enhanced 3D model accuracy. This advancement holds promise for dental professionals seeking precise digital modeling for diverse applications in dentistry.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10974223PMC
http://dx.doi.org/10.3390/s24061995DOI Listing

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