Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentation method of gray level CT images. The segmentation process is performed by using the Fuzzy C-Means (FCM) clustering method to detect and segment kidney CT images for the kidney region. The propose method is started with pre-processing of the kidney CT image to separate the kidney from the abdomen CT and to enhance its contrast and removing the undesired noise in order to make the image suitable for further processing. The resulted segmented CT images, then used to extract the tumor region from kidney image defining the tumor volume (size) is not an easy task, because the 2D tumor shape in the CT slices are not regular. To overcome the problem of calculating the area of the convex shape of the hull of the tumor in each slice, we have used the Frustum model for the fragmented data.
The aims of the lecture should be clearly defmed. These will help to define the teaching methods and the structure. If, for example, the purpose of the lecture is to introduce new knowledge and concepts, then a classic lecture structure might be most appropriate. On the other hand, if the purpose is to make the students aware of different approaches to a particular clinical problem, a problem oriented design in which alternative approaches are presented and discussed might be a more appropriate fonnat.
Lectures are still a common teaching methOd in both undergraduate and postgraduak medical education. Properly done, the lectwe is a creative and personal work by the teachll:l modeled upon his intellectual scaffolding. Few other fonns o
Background: Gugglusterone has been reported to provide protection against inflammatory and oxidative reactions of different pathological conditions. Objectives: The main object of this research work is to evaluate the renoprotective effects of guggulsterone in the prevention of cisplatin-induced nephrotoxicity in rats via assessment of renal function and histological study. Materials and methods: Rats in this study were split into four groups which comprise a control group, an induction group, a third group receiving low-dose guggulsterone, and a fourth group receiving high-dose guggulsterone. Results: a single dose of cisplatin drug has jeopardisedrenal physiology that has been demonstrated in histopathology sections and elevation
... Show MorePsychological research centers help indirectly contact professionals from the fields of human life, job environment, family life, and psychological infrastructure for psychiatric patients. This research aims to detect job apathy patterns from the behavior of employee groups in the University of Baghdad and the Iraqi Ministry of Higher Education and Scientific Research. This investigation presents an approach using data mining techniques to acquire new knowledge and differs from statistical studies in terms of supporting the researchers’ evolving needs. These techniques manipulate redundant or irrelevant attributes to discover interesting patterns. The principal issue identifies several important and affective questions taken from
... Show MoreEstimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling the Symmetric gray scale texture image and estimating by using
... Show MoreObjective(s): To determine the impact of the Electronic Health Information Systems upon medical, medical backing and administrative business fields in Al-Kindy Teaching Hospital and to identify the relationship between such impact and their demographic characteristics of years of employment, place of work, and education. Methodology: A descriptive analytical design is employed through the period of April 25th 2016 to May 28th 2016. A purposive "non- probability" sample of (50) subject is selected. The sample is comprised of (25) medical and medical backing staff and (25) administrative staff who are all
The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing. Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds. This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin
... Show MoreAlthough the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .
In this paper a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet
... Show MoreText based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.
... Show MoreEstimation of the tail index parameter of a one - parameter Pareto model has wide important by the researchers because it has awide application in the econometrics science and reliability theorem.
Here we introduce anew estimator of "generalized median" type and compare it with the methods of Moments and Maximum likelihood by using the criteria, mean square error.
The estimator of generalized median type performing best over all.