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Estimation of kidney tumor volume in CT images using medical image segmentation techniques
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Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentation method of gray level CT images. The segmentation process is performed by using the Fuzzy C-Means (FCM) clustering method to detect and segment kidney CT images for the kidney region. The propose method is started with pre-processing of the kidney CT image to separate the kidney from the abdomen CT and to enhance its contrast and removing the undesired noise in order to make the image suitable for further processing. The resulted segmented CT images, then used to extract the tumor region from kidney image defining the tumor volume (size) is not an easy task, because the 2D tumor shape in the CT slices are not regular. To overcome the problem of calculating the area of the convex shape of the hull of the tumor in each slice, we have used the Frustum model for the fragmented data.

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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
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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
Fri Nov 15 2024
Journal Name
Iraqi Journal Of Science
Direction of Arrival Estimation of Meteors Echoes using Array Radio Antennas
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Array antennas have an interesting role in the radio astronomy field. The array antennas allow astronomers to obtain high-resolution signals with high sensitivity to weak signals. This paper estimates the meteors' positions entering the Earth's atmosphere and develops a simulation for array antenna radar to analyze the meteor's echoes. The GNU radio software was used to process the echoes, which is a free open-source software development toolkit that provides signal processing blocks to implement in radio projects. Then, the simulation determines the azimuth and elevation of the meteors. An improved Multiple Signal Classification (MUSIC) algorithm has been suggested to analyze these echoes. The detected power of each meteor echo has

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Hypothyroidism and Leptin in Iraqi Patients with Chronic Kidney Disease
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The present study aims at assessing the effects of chronic kidney disease (CKD) on thyroid hormone and leptin by evaluating the level of: leptin hormone along with thyroid hormone in CKD patients. The study has been conducted on  70 subjects, 50 patients with an age range between 20-50 years (25  males and 25 females) who were diagnosed to have CKD stage-5, and 20 normal controls whose ages ranged between 20-48 years (10  males and 10 females), who attended  the Nephrology and Transplant Center in Medical City of Baghdad- Iraq from April  2018  to July  2018. The study showed a highly significant (P<0.01) increase in TSH level in CKD patients in comparison with controls. While T3 and T4 levels observed highly significant decrea

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Hypothyroidism and AMH in Iraqi Patients with Chronic Kidney Disease
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This study was conducted to investigate thyroid function and Anti-Müllerian hormone (AMH) in (Chronic kidney disease) CKD patients by evaluating their levels in CKD patients, 50 patients were diagnosed to have CKD stage-5, their ages ranged between 20-50 years (25 males and 25 females) who attended the Nephrology and Transplant Center in Medical City of Baghdad- Iraq, they were recruited from April 2018 to July 2018 and were enrolled into the study. The control group consisted of 20 healthy individuals, their ages ranged between 20-48 years (10 males and 10 females). The study showed non-significant (p>0.05) increase in AMH level in CKD patients compared to the control group. On the other hand, TSH was recorded a highly significant (

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Publication Date
Tue Jun 03 2025
Journal Name
Sar Journal Of Pathology And Microbiology
The Relation between Tumor Infiltrating Lymphocyte and Classical Tumor Staging in Colorectal Carcinoma (Semi-Quantitative Study by Immun histochemistry in a Group of Iraqi Patients)
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Inflammatory response had a role in cancer progression, presence of noticeable inflammation within the tumor and its margin may play an important prognostic role in colorectal carcinoma.

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Assessment of image quality of cervical spine complications using Three Magnetic Resonance Imaging Sequences
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Examining and comparing the image quality of degenerative cervical spine diseases through the application of three MRI sequences; the Two-Dimension T2 Weighed Turbo Spin Echo (2D T2W TSE), the Three-Dimension T2 Weighted Turbo Spin Echo (3D T2W TSE), and the T2 Turbo Field Echo (T2_TFE). Thirty-three patients who were diagnosed as having degenerative cervical spine diseases were involved in this study. Their age range was 40-60 years old. The images were produced via a 1.5 Tesla MRI device using (2D T2W TSE, 3D T2W TSE, and T2_TFE) sequences in the sagittal plane. The image quality was examined by objective and subjective assessments. The MRI image characteristics of the cervical spines (C4-C5, C5-C6, C6-C7) showed significant difference

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Publication Date
Wed Mar 23 2011
Journal Name
Ibn Al- Haitham J. For Pure & Appl. Sci.
Image Compression Using Proposed Enhanced Run Length Encoding Algorithm
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In this paper, we will present proposed enhance process of image compression by using RLE algorithm. This proposed yield to decrease the size of compressing image, but the original method used primarily for compressing a binary images [1].Which will yield increasing the size of an original image mostly when used for color images. The test of an enhanced algorithm is performed on sample consists of ten BMP 24-bit true color images, building an application by using visual basic 6.0 to show the size after and before compression process and computing the compression ratio for RLE and for the enhanced RLE algorithm.

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Publication Date
Fri Jun 23 2023
Journal Name
Al-mustansiriyah Journal Of Science
Image Encryption Using New Non-Linear Stream Cipher Cryptosystem
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In this paper, we designed a new efficient stream cipher cryptosystem that depend on a chaotic map to encrypt (decrypt) different types of digital images. The designed encryption system passed all basic efficiency criteria (like Randomness, MSE, PSNR, Histogram Analysis, and Key Space) that were applied to the key extracted from the random generator as well as to the digital images after completing the encryption process.

Publication Date
Tue Dec 31 2024
Journal Name
Journal Of Soft Computing And Computer Applications
Enhancing Image Classification Using a Convolutional Neural Network Model
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In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Merge Operation Effect On Image Compression Using Fractal Technique
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Fractal image compression gives some desirable properties like fast decoding image, and very good rate-distortion curves, but suffers from a high encoding time. In fractal image compression a partitioning of the image into ranges is required. In this work, we introduced good partitioning process by means of merge approach, since some ranges are connected to the others. This paper presents a method to reduce the encoding time of this technique by reducing the number of range blocks based on the computing the statistical measures between them . Experimental results on standard images show that the proposed method yields minimize (decrease) the encoding time and remain the quality results passable visually.

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