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During the acquisition on a low-dose radiation computed tomography (CT) scan, images are usually marked by heavy noise and undesired artifacts, which dramatically reduce its applicability in the image processing workflow. A noise reduction and detail preservation filter based on mathematical morphology is presented in this paper. The filter is geared to allow control of an opening operator followed by a systematic contrast limited adaptive histogram equalization (CLAHE) in conjunction with a reconstruction by dilation in last stage. A quantitative metric built on peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and mean-squared error (MSE) were applied to check noise reduction, detail preservation, and performance. The results obtained by the proposed filter were compared with those obtained in the literature, showing very good results: compared with the best-tested filter, the filter had a gain of 7.91% on PSNR, 7.57% on SSIM and 37.8% on MSE. [ABSTRACT FROM AUTHOR]

This paper has focused on improving the methodology to identify and control the new and persistent risks of injury and disease in the dental profession. The first step and key component of a health and safety program is to identify all situations or events that could affect the safety of workers in the dental profession. The methodology used benchmarking literature available but it also relied on personal experience and on a series of best practices and guidelines that describe methods for employers and employees to improve health and safety in the dental field. The research has allowed the preparation of lists that provide basic information about the biological, chemical, physical and psychosocial hazard, well as on the main control strategies for dental offices. The information contained in this paper is intended to serve as a guide for continuous improvement of OHS systems in the dental profession. [ABSTRACT FROM AUTHOR]

Possible application of the lichen genus Cladonia in dental practice due to antibacterial properties of lichen acids and enhanced bioavailability of obtained product after mechanochemical processing. [ABSTRACT FROM AUTHOR]

Dental radiography meets challenge to classify the dents into the proper class which useful for forensic and biomedical application. This paper proposed a novel method of classification and numbering on posterior dental radiography using support vector machine (SVM) with mesiodistal neck detection. In this method we developed SVM using a nouvelle feature with mesiodistal neck teeth. This feature was used to solve the problem in the dental image which suffered with completeness of whole part of teeth (crown-root). Preprocessing for enhancements included morphological operation, contrast adaptive, and tresholding. Every tooth has been assigned according to universal dental numbering and classified as their sequence order. Our system achieved classification precision of 90 %. This approach is robust and optimal for solving the problem of dental classification. [ABSTRACT FROM PUBLISHER]