Abstract
The confocal laser scanning microscopy (CLSM) system has been widely used to analyze early carious lesions with fluorescent ligands in dental imaging. This system can be used to examine the physiological condition of cellular colonization in the tooth structure. However, the undesirable noise in CLSM images hinders accurate activity assessment of early carious lesions. To address this limitation, a total variation (TV)-based noise reduction algorithm with good edge preservation was developed, and its applicability to medical tooth specimen images obtained with CLSM was verified. To evaluate the imaging performance, the proposed algorithm was compared with conventional filtering methods in terms of the normalized noise power spectrum, contrast-to-noise ratio, and coefficient of variation. The results indicate that the proposed algorithm achieved better noise performance and fine-detail preservation, in comparison with the conventional methods.
Highlights
In the fields of biomedicine and microbiology, fluorescence microscopy is employed to image proteins, tissues, and cells, which are otherwise impossible to observe with the naked eye
We investigated investigatedthe thefeasibility feasibilityofofthe the proposed algorithm images when applied for activity assessment of early carious lesions
Conventional light microscopy is limited by the achievable image quality, in terms of the Conventional light microscopy is limited by the achievable image quality, in terms of the resolution and noise performance, owing to fundamental factors
Summary
In the fields of biomedicine and microbiology, fluorescence microscopy is employed to image proteins, tissues, and cells, which are otherwise impossible to observe with the naked eye. It is difficult to accurately image a sample using a conventional fluorescence microscope. Confocal laser scanning microscopy (CLSM), which can achieve a higher resolution than that of a conventional fluorescence microscope, was introduced. A confocal laser scanning micrograph is constructed pixel-by-pixel by collecting the emitted photons from the fluorophores in the sample [1,2]. Based on this basic principle, CLSM provides images with higher resolution (approximately 1.4×).
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