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Texture Features Analysis using Gray Level Co-occurrence Matrix for Abnormality Detection in Chest CT Images

Texture is an important characteristic for the analysis of many types of images because it provides a rich source of information about the image. Also it provides a key to understand basic mechanisms that underlie human visual perception. In this paper four statistical feature of texture (Contrast, Correlation, Homogeneity and Energy) was calculated from gray level Co-occurrence matrix (GLCM) of equal blocks (30×30) from both tumor tissue and normal tissue of three samples of CT-scan image of patients with lung cancer. It was found that the contrast feature is the best to differentiate between textures, while the correlation is not suitable for comparison, the energy and homogeneity features for tumor tissue always greater than its values for normal tissue.

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Nurses' Knowledge About Chest Physiotherapy Techniques for Patients With Corona Virus Disease

Abstract

Objective(s): A descriptive study aimed to determine nurses' knowledge about chest physiotherapy techniques for patients with Corona virus disease and observe the relationship between nurses' knowledge and their socio-demographic characteristics.

Methodology: The study was directed in isolation units of Al- Hussein teaching hospitals in Thi-Qar, Iraq for the period from June 1st,  2022 to November 27th, 2022. Non- probability (purposively) sample comprised 41 nurses. A questionnaire was used for data collection and it consists of two parts: the first part comprises socio demographic features, the second part includes self- administered questionnaire sheet wa

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Publication Date
Wed Mar 01 2017
Journal Name
Un Published
Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Wavenet (FWN) classifier for medical images

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

&n

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Publication Date
Sat Jan 30 2021
Journal Name
Iraqi Journal Of Science
Intrusion Detection System Using Data Stream Classification

Secure data communication across networks is always threatened with intrusion and abuse. Network Intrusion Detection System (IDS) is a valuable tool for in-depth defense of computer networks. Most research and applications in the field of intrusion detection systems was built based on analysing the several datasets that contain the attacks types using the classification of batch learning machine. The present study presents the intrusion detection system based on Data Stream Classification. Several data stream algorithms were applied on CICIDS2017 datasets which contain several new types of attacks. The results were evaluated to choose the best algorithm that satisfies high accuracy and low computation time.

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Publication Date
Mon Feb 22 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
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Publication Date
Mon Feb 20 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Satellite Images Fusion Using Mapped Wavelet Transform Through PCA

In this paper a new fusion method is proposed to fuse multiple satellite images that are acquired through different electromagnetic spectrum ranges to produce a single gray scale image. The proposed method based on desecrate wavelet transform using pyramid and packet bases, the fusion process preformed using two different fusion rules, where the low frequency part is remapped through the use of PCA analysis basing on covariance matrix and correlation matrix, and the high frequency part is fused using different fusion rules (adding, selecting the higher, replacement), then the restored image is obtained by applying the inverse desecrate wavelet transform. The experimental results show the validity of the proposed fusion method to fuse suc

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Publication Date
Tue Jan 18 2022
Journal Name
Iraqi Journal Of Science
Restoration of Digital Images Using an Iterative Filter Algorithm

Digital image started to including in various fields like, physics science, computer science, engineering science, chemistry science, biology science and medication science, to get from it some important information. But any images acquired by optical or electronic means is likely to be degraded by the sensing environment. In this paper, we will study and derive Iterative Tikhonov-Miller filter and Wiener filter by using criterion function. Then use the filters to restore the degraded image and show the Iterative Tikhonov-Miller filter has better performance when increasing the number of iteration To a certain limit then, the performs will be decrease. The performance of Iterative Tikhonov-Miller filter has better performance for less de

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Publication Date
Thu Apr 28 2022
Journal Name
Iraqi Journal Of Science
Hybrid Images Compression and Transmitted Using MC-CDMA System

In this paper, the combined source coding with Multi Carrier Code Division Multiple Access (MC-CDMA) system is proposed, where the transmission of the compressed image produced from source coding through Additive White Gaussian Noise (AWGN) channel for a single user and multi users. In which the (MC-CDMA) system removes Inter Symbol Interference (ISI) and Inter Carrier Interference (ICI). The hybrid compression system of Discrete Cosine Transform (DCT) and predictive coding (PC) technique are integrated as a source coding. The simulation results indicates that the transmission system of a single user was much better than the transmission system of multi users. When the number of users increased, the Bit Error Rate (BER) increased. For a

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Publication Date
Sun May 15 2022
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
Publication Date
Sun Apr 01 2007
Journal Name
Journal Of The Faculty Of Medicine Baghdad
CT Evaluation of Liver Hydatid Disease

Background: To elucidate distinctive CT imaging features that allows a diagnosis of hepatic hydatidosis.
Patients and methods : The computed tomographic (CT) findings of 58 patients with sonographically detected cystic liver lesions were prospectively analyzed. These patients were
followed up until a final diagnosis was reached.
Results : By CT scanning we correctly localized and diagnosed 81 hepatic hydatid cysts in 50 patients. These were all proved by surgery or endoscopic retrograde cholangio-pancreatography (ERCP). Stage III and II hydatid cysts were the commonest types (29 % and 25 % respectively ). 52 % of the cysts were 5-10 cm at presentation. At CT, we identified some ancillary imaging fea

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