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Automatic brain tumor segmentation from MRI Images using superpixels based split and Merge algorithm
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RA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2

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Publication Date
Sat Apr 06 2024
Journal Name
Al- Anbar Medical Journal
Metastatic Ovarian Tumor from Incidental Renal Cell Carcinoma: A Case Report and Literature Review
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Publication Date
Tue Nov 03 2015
Journal Name
Journal Of Natural Sciences Research
Implementation of remote sensing for vegetation studying using vegetation indices and automatic feature space plot
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Publication Date
Wed Mar 01 2017
Journal Name
2017 Annual Conference On New Trends In Information & Communications Technology Applications (ntict)
Automatic Iraqi license plate recognition system using back propagation neural network (BPNN)
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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Educational And Psychological Researches
The Teaching Practices of Faculty Members in Northern Border University According to the Brain-Based Learning Theory
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The present study aims to identify the most and the least common teaching practices among faculty members in Northern Border University according to brain-based learning theory, as well as to identify the effect of sex, qualifications, faculty type, and years of experiences in teaching practices. The study sample consisted of (199) participants divided into 100 males and 99 females. The study results revealed that the most teaching practice among the study sample was ‘I am trying to create an Environment of encouragement and support within the classroom which found to be (4.4623). As for the least teaching practice was ‘I use a natural musical sounds to create student's mood to learn’ found to be (2.2965). The study results also in

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Improved Rijndael Algorithm by Encryption S-Box Using NTRU Algorithm
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With the wide developments of computer science and applications of networks, the security of information must be increased and make it more complex. The most important issues is how to control and prevent unauthorized access to secure information, therefore this paper presents a combination of two efficient encryption algorithms to satisfy the purpose of information security by adding a new level of encryption in Rijndael-AES algorithm. This paper presents a proposed Rijndael encryption and decryption process with NTRU algorithm, Rijndael algorithm is important because of its strong encryption. The proposed updates are represented by encryption and decryption Rijndael S-Box using NTRU algorithm. These modifications enhance the degree of

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Publication Date
Thu Jan 01 2015
Journal Name
Iraqi Journal Of Science
Improved Rijndael Algorithm by Encryption S-Box Using NTRU Algorithm
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With the wide developments of computer applications and networks, the security of information has high attention in our common fields of life. The most important issues is how to control and prevent unauthorized access to secure information, therefore this paper presents a combination of two efficient encryption algorithms to satisfy the purpose of information security by adding a new level of encryption in Rijndael-AES algorithm. This paper presents a proposed Rijndael encryption and decryption process with NTRU algorithm, Rijndael algorithm is widely accepted due to its strong encryption, and complex processing as well as its resistance to brute force attack. The proposed modifications are implemented by encryption and decryption Rijndael

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Publication Date
Fri Mar 20 2009
Journal Name
Ijcsns International Journal Of Computer Science And Network Security
Pre-processing Importance for Extracting Contours from Noisy Echocardiographic Images
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Contours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.

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Publication Date
Sun Oct 31 2021
Journal Name
Eastern-european Journal Of Enterprise Technologies
Distinguishing of different tissue types using K-Means clustering of color segmentation
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Millions of lives might be saved if stained tissues could be detected quickly. Image classification algorithms may be used to detect the shape of cancerous cells, which is crucial in determining the severity of the disease. With the rapid advancement of digital technology, digital images now play a critical role in the current day, with rapid applications in the medical and visualization fields. Tissue segmentation in whole-slide photographs is a crucial task in digital pathology, as it is necessary for fast and accurate computer-aided diagnoses. When a tissue picture is stained with eosin and hematoxylin, precise tissue segmentation is especially important for a successful diagnosis. This kind of staining aids pathologists in disti

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Publication Date
Mon Jun 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Breast Tumor Diagnosis Using Diode Laser in Near Infrared Region
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In the last years, new non-invasively laser methods were used to detect breast tumors for pre- and postmenopausal females. The methods based on using laser radiation are safer than the other daily used methods for breast tumor detection like X-ray mammography, CT-scanner, and nuclear medicine.  

      One of these new methods is called FDPM (Frequency Domain Photon Migration). It is based on the modulation of laser beam by variable frequency sinusoidal waves. The modulated laser radiations illuminate the breast tissue and received from opposite side.

      In this paper the amplitude and the phase shift of the received signal were calculated according to the orig

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Brain Tumour Detection using Fine-Tuning Mechanism for Magnetic Resonance Imaging
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In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

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