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Real-Time Dynamic Navigation System for the Precise Quad-Zygomatic Implant Placement in a Patient with a Severely Atrophic Maxilla
Published on: October 18, 2021
Image fusion-based low-dose CBCT enhancement method for visualizing miniscrew insertion in the infrazygomatic crest
Peipei Sun1,2, Jinghui Yang1,2, Xue Tian1,2
1State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
This study introduces a novel low-dose cone-beam computed tomography (CBCT) image enhancement method using image fusion. The technique improves visibility and contrast in dental CBCT scans, aiding subzygomatic small screw implantation.
Area of Science:
- Digital dentistry
- Medical imaging
- Image processing
Background:
- Low-dose cone-beam computed tomography (CBCT) in dentistry often suffers from poor image quality, including underexposure, overexposure, low visibility, and low contrast.
- These image quality issues can hinder accurate diagnosis and surgical planning, particularly for procedures like subzygomatic small screw insertion.
Purpose of the Study:
- To develop and validate a low-dose CBCT image enhancement method for dental applications.
- To improve the interpretability of oral CBCT images, specifically addressing issues of over/underexposure, low visibility, and low contrast.
- To facilitate precise subzygomatic small screw implantation through enhanced CBCT imaging.
Main Methods:
- A novel image fusion technique is proposed, integrating a sharpening correction module to compensate for detail loss in underexposed/overexposed regions.
- A visibility restoration module utilizing type II fuzzy sets and a contrast enhancement module employing curve transformation are designed.
- A perceptual fusion module combines the enhanced visibility and contrast information for comprehensive image improvement.
Main Results:
- The proposed method effectively addresses overexposure, underexposure, low visibility, and low contrast in oral CBCT images.
- Comparative and ablation experiments demonstrate superior performance compared to existing advanced enhancement algorithms.
- The enhancement algorithm achieved evaluation metric improvements of 0.07-2 on both datasets compared to the best-performing method.
Conclusions:
- The developed low-dose CBCT image enhancement method significantly improves image quality and interpretability for dental applications.
- The technique shows promise for enhancing the visualization required for subzygomatic small screw implantation.
- The proposed algorithm offers a robust solution for improving low-dose CBCT imaging in dentistry.
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