Developing an efficient algorithm for automated Magnetic Resonance Imaging (MRI) segmentation to characterize tumor abnormalities in an accurate and reproducible manner is ever demanding. This paper presents an overview of the recent development and challenges of the energy minimizing active contour segmentation model called snake for the MRI. This model is successfully used in contour detection for object recognition, computer vision and graphics as well as biomedical image processing including X-ray, MRI and Ultrasound images. Snakes being deformable well-defined curves in the image domain can move under the influence of internal forces and external forces are subsequently derived from the image data. We underscore a critical appraisal

In this paper, an adaptive medical image watermarking technique is proposed based on wavelet transform and properties of human visual system in order to maintain the authentication of medical images. Watermark embedding process is carried out by transforming the medical image into wavelet domain and then adaptive thresholding is computed to determine the suitable locations to hide the watermark in the image coefficients. The watermark data is embedded in the coefficients that are less sensitive into the human visual system in order to achieve the fidelity of medical image. Experimental results show that the degradation by embedding the watermark is too small to be visualized. Also, the proposed adaptive watermarking technique can preserv

In this paper, a simple medical image compression technique is proposed, that based on utilizing the residual of autoregressive model (AR) along with bit-plane slicing (BPS) to exploit the spatial redundancy efficiently. The results showed that the compression performance of the proposed techniques is improved about twice on average compared to the traditional autoregressive, along with preserving the image quality due to considering the significant layers only of high image contribution effects.

        In real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson” and the “Expectation-Maximization” techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

Fusion can be described as the process of integrating information resulting from the collection of two or more images from different sources to form a single integrated image. This image will be more productive, informative, descriptive and qualitative as compared to original input images or individual images. Fusion technology in medical images is useful for the purpose of diagnosing disease and robot surgery for physicians. This paper describes different techniques for the fusion of medical images and their quality studies based on quantitative statistical analysis by studying the statistical characteristics of the image targets in the region of the edges and studying the differences between the classes in the image and the calculation

Background: The human face has its special characteristics. It may be categorized into essentially three kinds in horizontal and vertical directions: short or brachyfacial, medium or mesofacial and long or dolichofacial. The aim of this study was to describe several orofacial indices and proportions of adults, according to gender in Iraqi subjects by using cone beam computed tomography . materials and methods: This prospective study included 100 Iraqi patients (males and females) ranging from 20 to 40 years. All subjects attended the Oral and Maxillofacial Radiology Department of Health Specialist Center for Dentistry in AL Sadr city in Baghdad taking cone beam computed tomography scan for different diagnostic purposes from October 2016 to

Fractional Er: YAG laser resurfacing is increasingly used for treating rhytides and photo aged skin because of its favorable benefit‐risk ratio. The multi-stacking and variable pulse width technology opened a wide horizon of rejuvenation treatments using this type of laser. To evaluate the efficacy and safety of the use of fractional 2940 nm Er: YAG laser in facial skin rejuvenation. Twelve female patients with mean age 48.3 years and multiple degrees of aging signs and solar skin damages, were treated with 2 sessions, one month apart by fractional Er: YAG laser. Each session consisted of 2 steps, the first step employed the use of the multi stack ablative fractional mode and the fractional long pulsed non-ablative mode settings were u