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Multi-planar 2.5D U-Net for image quality enhancement of dental cone-beam CT

 Kanghyun Ryu  ;  Chena Lee  ;  Yoseob Han  ;  Subeen Pang  ;  Young Hyun Kim  ;  Chanyeol Choi  ;  Ikbeom Jang  ;  Sang-Sun Han 
 PLOS ONE, Vol.18(5) : e0285608, 2023-05 
Journal Title
Issue Date
Artifacts ; Cone-Beam Computed Tomography / methods ; Humans ; Image Enhancement* ; Image Processing, Computer-Assisted / methods ; Imaging, Three-Dimensional* / methods ; Phantoms, Imaging ; Retrospective Studies
Cone-beam computed tomography (CBCT) can provide 3D images of a targeted area with the advantage of lower dosage than multidetector computed tomography (MDCT; also simply referred to as CT). However, in CBCT, due to the cone-shaped geometry of the X-ray source and the absence of post-patient collimation, the presence of more scattering rays deteriorates the image quality compared with MDCT. CBCT is commonly used in dental clinics, and image artifacts negatively affect the radiology workflow and diagnosis. Studies have attempted to eliminate image artifacts and improve image quality; however, a vast majority of that work sacrificed structural details of the image. The current study presents a novel approach to reduce image artifacts while preserving details and sharpness in the original CBCT image for precise diagnostic purposes. We used MDCT images as reference high-quality images. Pairs of CBCT and MDCT scans were collected retrospectively at a university hospital, followed by co-registration between the CBCT and MDCT images. A contextual loss-optimized multi-planar 2.5D U-Net was proposed. Images corrected using this model were evaluated quantitatively and qualitatively by dental clinicians. The quantitative metrics showed superior quality in output images compared to the original CBCT. In the qualitative evaluation, the generated images presented significantly higher scores for artifacts, noise, resolution, and overall image quality. This proposed novel approach for noise and artifact reduction with sharpness preservation in CBCT suggests the potential of this method for diagnostic imaging.

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2. College of Dentistry (치과대학) > Dept. of Oral and Maxillofacial Radiology (영상치의학교실) > 1. Journal Papers
Yonsei Authors
Lee, Chena(이채나) ORCID logo https://orcid.org/0000-0002-8943-4192
Han, Sang Sun(한상선) ORCID logo https://orcid.org/0000-0003-1775-7862
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