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Objective: In dental radiography, information distorted by scatter radiation and superimposition is reflected. There is a disadvantage that the discrimination is low, especially in the case of lowcontrast materials. To overcome this problem, a low-frequency component based contrast enhancement algorithm for radiographic images was established and implemented effectively. We assessed a sophisticated technique for identifying tooth, head, and neck structures using low-frequency components for dental professions. Methods: Based on a low-frequency component calculation using the Fourier transform and contrast enhancement model, we performed contrast enhancement using numerical phantom and intra-oral radiographic images. Results: The proposed method confirmed that the discrimination of internal materials with low contrast improved with simulation. The contrast-to-noise ratio of the proposed method was approximately 3.6 and 1.6 times higher than that of original and CLAHE imaging in intra-oral radiography, respectively. Conclusion: This study showed that the proposed approach provides a high ability to distinguish the entire dynamic range without controlling the window, and also significantly maintains the sharpness of the internal material. Increased expression in the area of tooth overlap, increased contrast of dentin, and improved detection of early caries were confirmed.
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Kim et al. (2024) studied this question.
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