Innovative Algorithms Enhance Detection of Peri-Implant Bone Defects on CBCT Scans

Posted: January 7, 2025
This study investigated the efficacy of metal artifact reduction (MAR) and advanced noise reduction (ANR) algorithms in detecting peri-implant bone defects using cone-beam computed tomography (CBCT) scans. The researchers found high inter-observer agreement for defect detection, with the combined use of MAR and ANR filters showing the highest diagnostic accuracy. However, activation of the ANR filter decreased specificity and positive predictive value. Understanding the impact of different algorithms on CBCT scans is crucial for accurate diagnosis and treatment planning in implant dentistry.

This article summary was generated by AI. To view the full article, click the link here: https://pubmed.ncbi.nlm.nih.gov/39773233/
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