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J Adv Periodontol Implant Dent. 2024;16(1): 1-3.
doi: 10.34172/japid.2024.011
  Abstract View: 101
  PDF Download: 62

Letter

Effect of auto-adaptive metal artifact reduction (aMAR) program in cone-beam computed tomography on assessing pre-implant bone levels

Farida Abesi* ORCID logo

1 Dental Materials Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
*Corresponding Author: Farida Abesi, Email: faridaabesi@yahoo.fr

Abstract

This research aimed to introduce an auto-adaptive metal artifact reduction (aMAR) algorithm in cone-beam computed tomography (CBCT) to assess the levels of the pre-implant alveolar crest. Dental implants as a treatment modality for edentulous patients consist of a titanium alloy, which creates a metal artifact, resulting in a dark dental structure in the CBCT scans. Metallic artifacts are limiting factors for the precise detection in CBCT images. These are related to the dark areas around materials and metallic structures (e.g., restorations, implants, and endodontic instruments). To overcome this problem, the metal artifact reduction (MAR) program has been recommended as a post-procedure stage for CBCT image reconstruction. Recent developments offer CBCT scanners with an aMAR option with a greater dynamic range to help overcome the challenges of peri-implant bone evaluation to reach accurate dental diagnoses.
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Submitted: 30 Apr 2024
Accepted: 18 May 2024
ePublished: 28 May 2024
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