Background: Transitional cell carcinoma of the urinary bladder is one of the important malignancies in both sex groups .It is considered as a heterogenous neoplasm with different
biological behavior, in which the majority are early non invasive with tendency for recurrence and some may progress to invasive tumor. An important clinicopathological features are ,the tumor stage and histological grade which are used as prognostic parameters of the tumor and play an important role in therapy. Due to the subjectivity of the histological grading , the reproducibility was low . Many studies showed the value of quantitative analysis of the tumor as an important method in determining the recurrence of the tumor and

In computer vision, visual object tracking is a significant task for monitoring
applications. Tracking of object type is a matching trouble. In object tracking, one
main difficulty is to select features and build models which are convenient for
distinguishing and tracing the target. The suggested system for continuous features
descriptor and matching in video has three steps. Firstly, apply wavelet transform on
image using Haar filter. Secondly interest points were detected from wavelet image
using features from accelerated segment test (FAST) corner detection. Thirdly those
points were descripted using Speeded Up Robust Features (SURF). The algorithm
of Speeded Up Robust Features (SURF) has been employed and impl

   Colonoscopy is a popular procedure which is used to detect an abnormality. Early diagnosis can help to heal many patients. The purpose of this paper is removing/reducing some artifacts to improve the visual quality of colonoscopy videos to provide better information for physicians. This work complements a series of work consisting of three previously published papers. In this paper, optic flow is used for motion compensation, where a number of consecutive images are registered to integrate some information to create a new image that has/reveals more information than the original one. Colon images were classified into informative and noninformative images by using a deep neural network. Then, two different strategies were use

    In this paper a method  to determine whether an image is forged (spliced) or not is presented. The proposed method is based on  a classification model to determine the authenticity of a tested image. Image splicing causes many sharp edges (high frequencies) and discontinuities to appear in the spliced image. Capturing these high frequencies in the wavelet domain rather than in the spatial domain is investigated in this paper. Correlation between high-frequency sub-bands coefficients of Discrete Wavelet Transform (DWT) is also described using co-occurrence matrix. This matrix was an input feature vector to a classifier. The best accuracy of 92.79% and 94.56% on Casia v1.0 and Casia v2.0 datasets respectively was achieved. This pe

Like the digital watermark, which has been highlighted in previous studies, the quantum watermark aims to protect the copyright of any image and to validate its ownership using visible or invisible logos embedded in the cover image. In this paper, we propose a method to include an image logo in a cover image based on quantum fields, where a certain amount of texture is encapsulated to encode the logo image before it is included in the cover image. The method also involves transforming wavelets such as Haar base transformation and geometric transformation. These combination methods achieve a high degree of security and robustness for watermarking technology. The digital results obtained from the experiment show that the values of Peak Sig

In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

In this paper, we define a cubic positive implicative-ideal, a cubic implicative-ideal and a cubic commutative-ideal of a semigroup in KU-algebra as a generalization of a fuzzy (positive implicative-ideal, an implicative-ideal and a commutative-ideal) of a semigroup in KU-algebra. Some relations between these types of cubic ideals are discussed. Also, some important properties of these ideals are studied. Finally, some important theories are discussed. It is proved that every cubic commutative-ideal, cubic positive implicative-ideal, and cubic implicative-ideal are a cubic ideal, but not conversely. Also, we show that if Θ is a cubic positive implicative-ideal and a cubic commutative-ideal then Θ is a cubic implicative-ideal. Some exam

    Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data.  This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −

This work is divided into two parts first part study electronic structure and vibration properties of the Iobenguane material that is used in CT scan imaging. Iobenguane, or MIBG, is an aralkylguanidine analog of the adrenergic neurotransmitter norepinephrine and a radiopharmaceutical. It acts as a blocking agent for adrenergic neurons. When radiolabeled, it can be used in nuclear medicinal diagnostic techniques as well as in neuroendocrine antineoplastic treatments. The aim of this work is to provide general information about Iobenguane that can be used to obtain results to diagnose the diseases. The second part study image processing techniques, the CT scan image is transformed to frequency domain using the LWT. Two methods of contrast

Image quality has been estimated and predicted using the signal to noise ratio (SNR). The purpose of this study is to investigate the relationships between body mass index (BMI) and SNR measurements in PET imaging using patient studies with liver cancer. Three groups of 59 patients (24 males and 35 females) were divided according to BMI. After intravenous injection of 0.1 mCi of 18F-FDG per kilogram of body weight, PET emission scans were acquired for (1, 1.5, and 3) min/bed position according to the weight of patient. Because liver is an organ of homogenous metabolism, five region of interest (ROI) were made at the same location, five successive slices of the PET/CT scans to determine the mean uptake (signal) values and its standard deviat