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Automatic brain tumor segmentation from MRI images using region growing algorithm
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LK Abood, RA Ali, M Maliki, International Journal of Science and Research, 2015 - Cited by 2

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Text Hiding in Color Images Using the Secret Key Transformation Function in GF (2n)
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Steganography is one of the most popular techniques for data hiding in the different media such as images, audio or video files. This paper introduced the improved technique to hide the secret message using the LSB algorithm inside the RGB true color image by encrypting it using the secret key transformation function. The key is selecting randomly in the GF (2n) with condition it has an inverse value to retrieve the encrypted message. Only two bits are used for the low byte in each pixel (the blue byte) to hide the secret message, since the blue color has a weak effect on human eyes. The message hidden by the suggested algorithm is less vulnerable to be stolen than other similar applications.

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Distinguishing Shapes of Breast Cancer Masses in Ultrasound Images by Using Logistic Regression Model
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The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

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Crossref
Publication Date
Tue Jan 01 2019
Journal Name
Advances In Computational Intelligence And Robotics
Groupwise Non-Rigid Image Alignment Using Few Parameters: Registration of Facial and Medical Images
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Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff

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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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Scopus (2)
Scopus
Publication Date
Mon Nov 29 2021
Journal Name
Iraqi Journal Of Science
The Effect of Using Inter-Frame Coding with Jpeg to Improve the Compression of Satellite Images
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Many recent satellite image compression methods depends on removing the spectral and spatial redundancies within image only , such these methods known as intra-frame(image) coding such as predictive and transformed based techniques , but these contributions needs a hard work in order to improve the compression performance also most of them are applied on individual data. The other trend is to exploit the temporal redundancy between the successive satellite images captured for the same area from different views, different sensors, or at different times, which will be much correlated and removing this redundancy will improve the compression performance and this principle known as inter-frame(image) coding .In this paper, a latest powerful

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Crossref
Publication Date
Sun Jul 31 2022
Journal Name
Iraqi Journal Of Science
A Prediction of Skin Cancer using Mean-Shift Algorithm with Deep Forest Classifier
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      Skin cancer is the most serious health problems in the globe because of its high occurrence compared to other types of cancer. Melanoma and non-melanoma are the two most common kinds of skin cancer. One of the most difficult problems in medical image processing is the automatic detection of skin cancer. Skin melanoma is classified as either benign or malignant based on the results of this test. Impediment due to artifacts in dermoscopic images impacts the analytic activity and decreases the precision level. In this research work, an automatic technique including segmentation and classification is proposed. Initially, pre-processing technique called DullRazor tool is used for hair removal process and semi-supervised mean-shift

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Scopus (2)
Crossref (1)
Scopus Crossref
Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
Maxillary Ameloblastic Fibroma: Two Case Reports of a Rare Tumor
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Ameloblastic fibroma is a rare benign tumor usually affects the first two decades of life. The neoplasm is more predominant in mandibular molar-premolar region and rarely affects the maxilla. In this report, we present a couple of Ameloblastic fibroma cases, affecting boys at their 1st decade. The lesions were presented as swellings of their maxilla, which is atypical location. Radiographic images showed well-defined radiolucency containing areas of radio-opacities and impacted teeth. Differential diagnosis was established as cystic/neoplastic conditions. The lesions were incised and histopathologically diagnosed as Ameloblastic fibroma, since they were composed of immature odontogenic mesenchymal and epithelial cells showing different c

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Scopus Crossref
Publication Date
Mon Jun 20 2022
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
DESCRIPTION OF THE PREDATOR BUSH CRICKET, SAGA EPHIPPIGERA FISCHER VON WALDHEIM, 1846 (ORTHOPTERA, TETTIGONIIDAE) FROM ERBIL PROVINCE, KURDISTAN REGION- IRAQ
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The predatory bush crickets Saga ephippigera Fischer Von Waldheim, 1846 is the largest Iraqi orthopterans and one of the most active and successful predators in the Kurdistan region. The nymphs and adults prey on all the stages of various species of insects. Twelve adult specimens were collected from Erbil Province during May 2018 and June 2021. Morphological structures of the adult insects were described and illustrated in details; important taxonomic characteristics of body regions with their appendages were chosen; and the results indicated the importance of morphological characteristics which confirmed the identification of this species correctly.

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Scopus Crossref
Publication Date
Thu Sep 28 2023
Journal Name
International Journal Of Membrane Science And Technology
Morphological and Anatomical Study of Some Species of Ziziphus L. (Rhamnaceae) Growing in Iraq
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The genus Ziziphus is one of the Family Rhamnaceae and consists of more than 170 species distributed in tropical and subtropical regions. All the species in the genus are of economical and medical importance. This study was conducted to identify the morphologically and anatomically features of the genus in Iraq.  The field survey was conducted across the study area where 4 species (Ziziphus jujube, Z. mauritiana, Z. nummularia and Z. spina-christi) were collected and used in the study.  The result showed that there is variation in morphological and anatomical features among the species in the stem cross-section and longitudinal section of leaves also the differences appeared in the epidermis of leaves.

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Crossref
Publication Date
Wed May 01 2019
Journal Name
Iraqi Journal Of Science
White Blood Cells Nuclei Localization Using Modified K-means Clustering Algorithm and Seed Filling Technique
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The presence of White Blood Cells (WBCs) in the body of human has a great role in the protection of the body against many pathogens. The recognition of the WBC is the first important step to diagnose some particular diseases. The pathologists usually use an optical microscope to recognize WBCs, but, this process is a quite tedious, time-consuming, error prone, very slow, and expensive. In addition, it needs experts with long practice in this field. For these reasons, a computer assisted diagnostic system that helps pathologists in the process of diagnosis can be effective, easy and safe. This research is devoted to develop a system based on digital image processing methods to localize WBCs nuclei. The proposed system involved a collectio

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