Background: Diagnosis and treatment planning can be difficult with conventional radiographic methods as the orthodontic-surgical management of impacted canines requires accurate diagnosis and precise localization of the impacted canine and the surrounding structures. This study was aimed to localize and evaluate weather there is any differences in the diagnostic information provided by multi-slice computed tomography three dimensional volumetric CT images and two dimensional reconstructed panorama images (derived from CT) in subjects with impacted maxillary canines. Materials and Methods: Thirty patients including 24 female and 6 male with mean age of 18 years with suspected unilaterally or bilaterally impacted maxillary canines were evaluated on images taken with Brilliance™ 64, Philips multi-detector computed tomography. The spatial relationships of the impacted maxillary canines relative to the adjacent structures was evaluated using linear and angular measurements, and the adjacent lateral incisor root resorption was assessed with three dimensional and two dimensional visualization software. Results: The inclination of the impacted maxillary canine measured to the midline and to the occlusal plane did not differ significantly when it was evaluated using the two imaging modalities. However, there were significant differences between the 3D and 2D images with respect to the impacted maxillary canine vertical height, bucco-palatal localization, and in detecting the proximity and root resorption of the adjacent lateral incisors. Conclusion: Dental CT volumetric images provide more reliable and accurate information for diagnosing the maxillary impacted canine position, inclination, distance from adjacent structures, and detection of lateral incisors rootresorption.
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Fractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal ima
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Fractal image compression gives some desirable properties like fast decoding image, and very good rate-distortion curves, but suffers from a high encoding time. In fractal image compression a partitioning of the image into ranges is required. In this work, we introduced good partitioning process by means of merge approach, since some ranges are connected to the others. This paper presents a method to reduce the encoding time of this technique by reducing the number of range blocks based on the computing the statistical measures between them . Experimental results on standard images show that the proposed method yields minimize (decrease) the encoding time and remain the quality results passable visually.
In this paper, a computational method for solving optimal problem is presented, using indirect method (spectral methodtechnique) which is based on Boubaker polynomial. By this method the state and the adjoint variables are approximated by Boubaker polynomial with unknown coefficients, thus an optimal control problem is transformed to algebraic equations which can be solved easily, and then the numerical value of the performance index is obtained. Also the operational matrices of differentiation and integration have been deduced for the same polynomial to help solving the problems easier. A numerical example was given to show the applicability and efficiency of the method. Some characteristics of this polynomial which can be used for solvin
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Optical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using M
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