Noise-Optimized CBCT Imaging of Temporomandibular Joints—The Impact of AI on Image Quality

Noise-Optimized CBCT Imaging of Temporomandibular Joints—The Impact of AI on Image Quality

<b>Background:</b> Temporomandibular joint disorder (TMD) is a common medical condition. Cone beam computed tomography (CBCT) is effective in assessing TMD-related bone changes, but image noise may impair diagnosis. Emerging deep learning reconstruction algorithms (DLRs) could minimize n...

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Bibliographic Details
Main Authors: Wojciech Kazimierczak, Kamila Kędziora, Joanna Janiszewska-Olszowska, Natalia Kazimierczak, Zbigniew Serafin
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Journal of Clinical Medicine
Subjects:
cone beam computed tomography
deep learning model
image quality
noise reduction
dental imaging
temporomandibular joint
Online Access:https://www.mdpi.com/2077-0383/13/5/1502

Internet

https://www.mdpi.com/2077-0383/13/5/1502

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