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Textural Analysis of Liver Tumor using Watershed Segmentation based on Statistical and Geometrical features

The liver diseases can define as the tumor or disorder that can affect the liver and causes deformation in its shape. The early detection and diagnose of the tumor using CT medical images, helps the detector to specify the tumor perfectly. This search aims to detect and classify the liver tumor depending on the use of a computer (image processing and textural analysis) helps in getting an accurate diagnosis. The methods which are used in this search depend on creating a binary mask used to separate the liver from the origins of the other in the CT images. The threshold has been used as an early segmentation. A Process, the watershed process is used as a classification technique to isolate the tumor which is cancer and cyst.

 The test images are taking five for cancer case and five for the cyst, the geometrical and statistical features are calculated for both cases to identify the identity for each case. The statistical features are obtained from the gray level co-occurrence matrix which is contrast, homogeneity, correlation and energy. The geometrical features are the area of the tumor, the circumference and irregularity. The irregularity tends to lose one of the cyst cases than for cancer because of its shape in more regular than cancer.

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Engineering
Ultrafiltration and Reverse Osmosis Membranes for Treating Wastewater Effluent from Gas Turbine Power Plants using the Statistical Method of Taguchi

A study on the treatment and reuse of oily wastewater generated from the process of fuel oil treatment of gas turbine power plant was performed. The feasibility of using hollow fiber ultrafiltration (UF) membrane and reverse osmosis (RO) membrane type polyamide thin-film composite in a pilot plant was investigated. Three different variables: pressure (0.5, 1, 1.5 and 2 bars), oil content (10, 20, 30 and 40 ppm), and temperature (15, 20, 30 and 40 ᵒC) were employed in the UF process while TDS was kept constant at 150 ppm. Four different variables: pressure (5, 6, 7 and 8 bar), oil content (2.5, 5, 7.5 and 10 ppm), total dissolved solids (TDS) (100, 200,300 and 400 ppm), and temperature (15, 20, 30 and 40 ᵒC) were mani

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Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
Maxillary Ameloblastic Fibroma: Two Case Reports of a Rare Tumor

Ameloblastic fibroma is a rare benign tumor usually affects the first two decades of life. The neoplasm is more predominant in mandibular molar-premolar region and rarely affects the maxilla. In this report, we present a couple of Ameloblastic fibroma cases, affecting boys at their 1st decade. The lesions were presented as swellings of their maxilla, which is atypical location. Radiographic images showed well-defined radiolucency containing areas of radio-opacities and impacted teeth. Differential diagnosis was established as cystic/neoplastic conditions. The lesions were incised and histopathologically diagnosed as Ameloblastic fibroma, since they were composed of immature odontogenic mesenchymal and epithelial cells showing different c

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Publication Date
Fri Mar 15 2024
Journal Name
Journal Of Baghdad College Of Dentistry
A clinicopathological analysis of 151 odontogenic tumors based on new WHO classification 2022: A retrospective cross-sectional study

Background: Odontogenic tumors are a diverse group of lesions with a variety of clinical behavior and histopathologic subtypes, from hamartomatous and benign to malignant. The study aimed to examine the clinical and pathological features of odontogenic tumors in Baghdad over the last 11 years (2011–2021). Materials and Methods: The present retrospective study analyzed all formalin-fixed, paraffin-embedded tissue blocks of patients diagnosed with an odontogenic tumor that were retrieved from archives at a teaching hospital/College of Dentistry in Baghdad University, Iraq, between 2011 and 2021. The diagnosis of each case was confirmed by examining the hematoxylin and eosin stained sections by two expert pathologists. Data from pati

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Publication Date
Wed May 25 2022
Journal Name
Iraqi Journal Of Science
Stopping power of Hetero nuclear di-cluster ions from partial-wave analysis based on semi classical phase shifts

 

We apply a semi classical partial-wave scattering method based on the induced density approach (IDA) model. For ion electron scattering, the transport cross section is used to calculate the energy loss. This method yields a non-perturbative exemplification of energy loss, bridging the difference among classical and quantal representations. The focus of this work is the interaction of hetero nuclear di-cluster (He-H) ions with a free gas. The results show three kinds of stopping power in (a.u) (cluster stopping power, self-stopping power and correlated stopping power) of hetero nuclear di-cluster ions (He-H) with velocity at different atomic di-cluster distances at different densities and temperatures. We find that Bragg’

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Review Study of E-Voting System Based on Smart Contracts Using Blockchain Technology

Voting is an important procedure in democratic societies in different countries, including Iraq. Electronic voting (E-voting) is becoming more prevalent due to reducing administrative costs and burdens. E-voting systems have many restrictions that affect the electoral process. For example, fraud, tampering with ballot boxes, taking many hours to announce results, and the difficulty of reaching polling stations. Over the last decade, blockchain and smart contract technologies have gained widespread adoption in various sectors, such as cryptocurrencies, finance, banking, and most notably in e-voting systems. If utilized properly, the developer demonstrates properties that are promising for their properties, such as security, privacy, trans

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Publication Date
Wed Apr 01 2020
Journal Name
Plant Archives
Land cover change detection using satellite images based on modified spectral angle mapper method

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

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Publication Date
Sun Jun 01 2014
Journal Name
International Journal Of Physics And Research (ijpr)
CALCULATIONS OF MOLTIPOLE MIXING RATIOS FOR GAMMA TRANSITIONS OF Yb POPULATED FROM Yb REACTION USING -RATIO, CONSTANT STATISTICAL TENSOR AND LEAST SQUARES FITTING METHODS

The - mixing ratios of -transitions from levels in populated in the reactions are calculated in present work using - ratio, constant statisticalTensor and least squares fitting methods The results obtained are in general, in good agreement or consistent, within the associated uncertainties, with these reported in Ref.[9],the discrepancies that occurs are due to inaccuracy existing in the experimental data The results obtained in the present work confirm the –method for mixed transitions better than that for pure transition because this method depends only on the experimental data where the second method depends on the pure or those considered to be pure -transitions, the same results occur in – method

Publication Date
Wed May 01 2019
Journal Name
Reports Of Practical Oncology & Radiotherapy
Estimation of tumor and local tissue dose in gold nanoparticles radiotherapy for prostate cancer

The objective of this research was to estimate the dose distribution delivered by radioactive gold nanoparticles (198 AuNPs or 199 AuNPs) to the tumor inside the human prostate as well as to normal tissues surrounding the tumor using the Monte-Carlo N-Particle code (MCNP-6.1. 1 code). Background Radioactive gold nanoparticles are emerging as promising agents for cancer therapy and are being investigated to treat prostate cancer in animals. In order to use them as a new therapeutic modality to treat human prostate cancer, accurate radiation dosimetry simulations are required to estimate the energy deposition in the tumor and surrounding tissue and to establish the course of therapy for the patient. Materials and methods A simple geometrical

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Iraqi Sentiment and Emotion Analysis Using Deep Learning

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Image Splicing Detection Based on Discrete Wavelet Transform and co-occurrence Matrix

    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

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