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Classification of Optical Images of Cervical Lymph Node Cells
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Abstract<p>the study considers the optical classification of cervical nodal lymph cells and is based on research into the development of a Computer Aid Diagnosis (CAD) to detect the malignancy cases of diseases. We consider 2 sets of features one of them is the statistical features; included Mode, Median, Mean, Standard Deviation and Maximum Probability Density and the second set are the features that consist of Euclidian geometrical features like the Object Perimeter, Area and Infill Coefficient. The segmentation method is based on following up the cell and its background regions as ranges in the minimum-maximum of pixel values. The decision making approach is based on applying of Minimum Distance which give accuracy of 97%.</p>
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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Differentiation of Adipose-Derived Mesenchymal Stem Cells into Neuron-Like Cells induced by using β-mercaptoethanol
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Background: Adipose derived-mesenchymal stem cells have been used as an alternative to bone marrow cells in this study. Objective: We investigated the in vitro isolation, identification, and differentiation of stem cells into neuron cells, in order to produce neuron cells via cell culture, which would be useful in nerve injury treatment. Method: Mouse adipose mesenchymal stem cells were dissected from the abdominal subcutaneous region. Neural differentiation was induced using β-mercaptoethanol. This study included two different neural stage markers, i.e. nestin and neurofilament light-chain, to detect immature and mature neurons, respectively. Results: The immunocytochemistry results showed that the use of β-mercaptoethanol resulted in

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Hiding Information Using different lighting Color images
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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Wavenet (FWN) classifier for medical images
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    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
Fri Sep 15 2023
Journal Name
Al-academy
The aesthetic images in Mohammed Thanoun graphic
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The tagged search (The aesthetic images in Mohammed Thanoun graphic) four chapters, Chapter I was concerned the statement of the research problem, the research importance and it’s needed, the goal of research in identifying the aesthetic images in the graphic of the artist's, the research limits, and identifying the most important terms, chapter II came with theoretical framework and included three chapters: chapter I was interested in the aesthetic concept. chapter II is the image aesthetic in the graphic, and chapter III is the artist experience, Chapter III specializes in research procedures: community, sample, curriculum, tool, and sample analysis. Chapter IV ended with results, including: dynamic research sample illustrated of the

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
The Satellite Images Matching and Mosaic Techniques
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      The Matching and Mosaic of the satellite imagery play an essential role in many remote sensing and image processing projects. These techniques must be required in a particular step in the project, such as remotely change detection applications and the study of large regions of interest. The matching and mosaic methods depend on many image parameters such as pixel values in the two or more images, projection system associated with the header files, and spatial resolutions, where many of these methods construct the matching and mosaic manually. In this research, georeference techniques were used to overcome the image matching task in semi automotive method. The decision about the quality of the technique can be considered i

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Publication Date
Thu Oct 01 2020
Journal Name
Biochemical And Cellular Archives
THE ONCOGENIC EFFECT OF EBV/HPV CO-INFECTION IN A GROUP OF IRAQI WOMEN WITH CERVICAL CARCINOMA
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The current paper was designed to find the possible synergic effect of EBV infection with the HPV-16 in Iraqi women suffering from cervical carcinoma. This retrospective study involved paraffinized blocks of two groups. The research included 30 carcinomatous cervical tissues and 15 samples from normal cervical biopsies. After sectioning using positively charged slides, immunohistochemistry (IHC) was performed to detect anti-Epstein Barr Virus LMP1 and Human papillomavirus type 16 primary antibodies. Sixty-three percentage (19 out of 30) of the studies group showed positive overexpression as shown in with a significant association of the expression with cervical cancer with a significant association (p = 0). The co-infection of the EBV and H

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Publication Date
Tue Jan 01 2019
Journal Name
Biochemical And Cellular Archives
Effect of HPV infection on the expression of fibronectin in a group of Iraqi women with cervical carcinoma
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: Cervical malignancy positioned as the fourth most prevalent disease among women around the world. HPVs especially HPV16 are the causative agent of cervical cancer, responsible of about 5% of all human cancers worldwide. Some researchers found that the fibronectin is repressed by the papillomavirus (HPV) type 16 E7 oncoprotein in both HPV-positive nontumorigenic and tumorigenic cell lines, while others found that the HPV oncoprotein increase the levels of fibronectin. The aim is to study the effect of HPV infection on Fibronectin expression and their correlation onthe development of Cervicalcancinoma. The current retrospective study enrolled paraffinized blocks of two groups. The research included 30 cervical carcinomatous tissues as well

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Publication Date
Tue Jun 01 2021
Journal Name
Iraqi Journal Of Physics
Studying Audio Capacity as Carrier of Secret Images in Steganographic System
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Steganography art is a technique for hiding information where the unsuspicious cover signal carrying the secret information. Good steganography technique must be includes the important criterions robustness, security, imperceptibility and capacity. The improving each one of these criterions is affects on the others, because of these criterions are overlapped each other.  In this work, a good high capacity audio steganography safely method has been proposed based on LSB random replacing of encrypted cover with encrypted message bits at random positions. The research also included a capacity studying for the audio file, speech or music, by safely manner to carrying secret images, so it is difficult for unauthorized persons to suspect

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Self-Localization of Guide Robots Through Image Classification
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The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

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Publication Date
Sun Apr 23 2017
Journal Name
International Conference Of Reliable Information And Communication Technology
Classification of Arabic Writer Based on Clustering Techniques
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Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

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