The estimation of the standard deviation of noise contaminating an image is a fundamental step in wavelet-based noise reduction techniques. The method widely used is based on the mean absolute deviation (MAD). This model-based method assumes specific characteristics of the noise-contaminated image component. Three novel and alternative methods for estimating the noise standard deviation are proposed in this work and compared with the MAD method. Two of these methods rely on a preliminary training stage in order to extract parameters which are then used in the application stage. The sets used for training and testing, 13 and 5 images, respectively, are fully disjoint. The third method assumes specific statistical distributions for image and noise components. Results showed the prevalence of the training-based methods for the images and the range of noise levels considered

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Many real word images are contaminated by noise. The noise not only degrades image quality but may also hinder further processing operations. Noise reduction techniques aim to both improve image quality and to aid further image processing. Spatial noise reduction techniques based on the discrete wavelet transform have been widely researched. This paper considers an undecimated shift invariant filter bank that has been used to decompose the image into components. The basic filters are derived from a biorthogonal wavelet basis. Reconstruction is obtained by a simple summation of the image components. A new thresholding scheme, which is obtained from Bayesian estimator theory, is used. The threshold parameters for each component are dependent on the noise level and are selected using a preliminary training procedure. The cost function utilised for the training is a weighted version of the mean square error which is designed to reflect human perception. The method compares favourably with other wavelet based noise reduction techniques and demonstrates significant noise reduction and visual quality enhancement.

Background: The aim is to demonstrate the validity of the monitoring through intraoral scanner of the dental movements and the real impact, advantages, and convenience, in terms of treatment time and efficiency gain, to frequently monitor a patient with the scanner application. Methods: A movement control of palatally impacted canines was performed, surgically treated with laser opercolectomy. Three-dimensional models of the patient’s dental arch were obtained with intraoral scanner during a monitoring time of 4 months. The STL (Standard Triangle Language) files were superimposed with the 3D models extrapolated from the pre-operative CT (Computerized Tomography). The measurements of eruption, exposed palatal and vestibular areas, and distances between the canines and the incisors were performed, using digital technologies and with a digital caliber. Results: Descriptive and inferential statistical analysis of the data obtained from both conventional and digital monitoring has been realized and performing the T Student Test for paired data. Conclusion: The advantages of digital monitoring are numerous, like the possibility to reduce the error of method caused by manual measurement on plaster casts and the possibility to compare the pattern and amount of eruption of the canine in the same patient overtime.

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Bifid or trifid mandibular condyle is an extremely rare entity, of unknown etiology, although it has been associated with trauma in the condyle growth center. The development of imagining techniques has allowed the exact characterization of these alterations, which were incidentally discovered by routine dental x-rays. The aim of this report is to describe a case of a mandibular condyle with a trifid appearance in a twelve year-old individual with a history of mandibular trauma during childhood and a review of the relevant literature.

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