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CT Image Segmentation Based on clustering Methods.

Background: image processing of medical images is major method to increase reliability of cancer diagnosis.
Methods: The proposed system proceeded into two stages: First, enhancement stage which was performed using of median filter to reduce the noise and artifacts that present in a CT image of a human lung with a cancer, Second: implementation of k-means clustering algorithm.
Results: the result image of k-means algorithm compared with the image resulted from implementation of fuzzy c-means (FCM) algorithm.
Conclusion: We found that the time required for k-means algorithm implementation is less than that of FCM algorithm.MATLAB package (version 7.3) was used in writing the programming code of our work.

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Publication Date
Tue Aug 31 2021
Journal Name
Iraqi Journal Of Science
Development of a Job Applicants E-government System Based on Web Mining Classification Methods

     Governmental establishments are maintaining historical data for job applicants for future analysis of predication, improvement of benefits, profits, and development of organizations and institutions. In e-government, a decision can be made about job seekers after mining in their information that will lead to a beneficial insight. This paper proposes the development and implementation of an applicant's appropriate job prediction system to suit his or her skills using web content classification algorithms (Logit Boost, j48, PART, Hoeffding Tree, Naive Bayes). Furthermore, the results of the classification algorithms are compared based on data sets called "job classification data" sets. Experimental results indicate

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Residual Network with Attention to Neural Cells Segmentation

      Many neuroscience applications, including understanding the evolution of the brain, rely on neural cell instance segmentation, which seeks to integrate the identification and segmentation of neuronal cells in microscopic imagery. However, the task is complicated by cell adhesion, deformation, vague cell outlines, low-contrast cell protrusion structures, and background imperfections. On the other hand, existing segmentation approaches frequently produce inaccurate findings. As a result, an effective strategy for using the residual network with attention to segment cells is suggested in this paper. The segmentation mask of neural cells may be accurately predicted. This method is built on U-net, with EfficientNet serving as the e

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Publication Date
Sun Oct 03 2010
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Malignant features of Meningioma CT scan Study.

CT scan features of Malignant Meningioma
Objective: Meningioma which is a common benign Brain tumor can be malignant, but the final decision is by biopsy. However CT. Scan features can help to evaluate malignancy of a lesion.

The aim of this retrospective study is to look for the malignant features of a malignant meningioma .
Patients and Methods: This is a retrospective study of 50 malignant meningiomas in the neurosurgical unit in the specialized surgical hospital (previously AL-Shaheed Adnan hospital), for the period from March 1992 to March 2007. We search specially for Malignant features on the CT scan study of the patients.
Results: 94%of the patients had different features of malignant men

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Publication Date
Fri Feb 17 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deploying Facial Segmentation Landmarks for Deepfake Detection

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
A Hybrid Algorithms Based on the Aizawa Attractor and Rabbit-Lightweight Cipher for Image Encryption

     Social media and networks rely heavily on images. Those images should be distributed in a private manner. Image encryption is therefore one of the most crucial components of cyber security. In the present study, an effective image encryption technique is developed that combines the Rabbit Algorithm, a simple algorithm, with the Attractor of Aizawa, a chaotic map. The lightweight encryption algorithm (Rabbit Algorithm), which is a 3D dynamic system, is made more secure by the Attractor of Aizawa. The process separates color images into blocks by first dividing them into bands of red, green, and blue (RGB). The presented approach generates multiple keys, or sequences, based on the initial parameters and conditions, which are

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Evaluation Tv- Image Quality for Different Cable Signal Transmission Resistance Based on Contrast Edge Algorithm

Some degree of noise is always present in any electronic device that
transmits or receives a signal . For televisions, this signal i has been to s the
broadcast data transmitted over cable-or received at the antenna; for digital
cameras, the signal is the light which hits the camera sensor. At any case, noise
is unavoidable. In this paper, an electronic noise has been generate on
TV-satellite images by using variable resistors connected to the transmitting cable
. The contrast of edges has been determined. This method has been applied by
capturing images from TV-satellite images (Al-arabiya channel) channel with
different resistors. The results show that when increasing resistance always
produced higher noise f

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Publication Date
Mon Jan 01 2024
Journal Name
International Journal Of Research In Science And Technology
Encryption of Medical Image Based on Cascaded Design of AES Block Algorithm and Chaotic Map

Security concerns in the transfer of medical images have drawn a lot of attention to the topic of medical picture encryption as of late. Furthermore, recent events have brought attention to the fact that medical photographs are constantly being produced and circulated online, necessitating safeguards against their inappropriate use. To improve the design of the AES algorithm standard for medical picture encryption, this research presents several new criteria. It was created so that needs for higher levels of safety and higher levels of performance could be met. First, the pixels in the image are diffused to randomly mix them up and disperse them all over the screen. Rather than using rounds, the suggested technique utilizes a cascad

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Publication Date
Wed Jul 06 2022
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Pixel Based Techniques for Gray Image Compression: A review

Currently, with the huge increase in modern communication and network applications, the speed of transformation and storing data in compact forms are pressing issues. Daily an enormous amount of images are stored and shared among people every moment, especially in the social media realm, but unfortunately, even with these marvelous applications, the limited size of sent data is still the main restriction's, where essentially all these applications utilized the well-known Joint Photographic Experts Group (JPEG) standard techniques, in the same way, the need for construction of universally accepted standard compression systems urgently required to play a key role in the immense revolution. This review is concerned with Different

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Publication Date
Fri Jan 01 2021
Journal Name
Cogent Engineering
Content-based image retrieval: A review of recent trends

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
IMPROVED IMAGE COMPRESSION BASED WAVELET TRANSFORM AND THRESHOLD ENTROPY

In this paper, a method is proposed to increase the compression ratio for the color images by
dividing the image into non-overlapping blocks and applying different compression ratio for these
blocks depending on the importance information of the block. In the region that contain important
information the compression ratio is reduced to prevent loss of the information, while in the
smoothness region which has not important information, high compression ratio is used .The
proposed method shows better results when compared with classical methods(wavelet and DCT).

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