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Medical Image Segmentation using Modified Interactive Thresholding Technique
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Medical image segmentation is one of the most actively studied fields in the past few decades, as the development of modern imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT), physicians and technicians nowadays have to process the increasing number and size of medical images. Therefore, efficient and accurate computational segmentation algorithms become necessary to extract the desired information from these large data sets. Moreover, sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures presented in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning. Many of the proposed algorithms could perform well in certain medical image applications.The aim of this paper is to change the medical image into something that is more meaningful and easier to analyze and recognize features that helps the doctors to diagnoses the diseases .This paper views selected medical image and segmentation method that have been proposed, which are suitable for processing medical images by use the modification of the traditional interactive threshold technique. This method gave good results,and these results are testedaccordingto the measure of quality (PSNR).

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Publication Date
Wed Dec 01 2021
Journal Name
Iraqi Journal Of Physics
Optical, Structural, Morphological Properties of Chromium (III) Oxide Nanostructure Synthesized Using Spray Pyrolysis Technique
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Nanostructure of chromium oxide (Cr2O3-NPs) with rhombohedral structure were successfully prepared by spray pyrolysis technique using Aqueous solution of Chromium (III) chloride CrCl3 as solution. The films were deposited on glass substrates heated to 450°C using X-ray diffraction (XRD) shows the nature of polycrystalline samples. The calculated lattice constant value for the grown Cr2O3 nanostructures is a = b = 4.959 Å & c = 13.594 Å and the average crystallize size (46.3-55.6) nm calculated from diffraction peaks, Spectral analysis revealed FTIR peak characteristic vibrations of Cr-O Extended and Two sharp peaks present at 630 and 578 cm-1 attributed to Cr-O “stretching

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Publication Date
Wed May 10 2017
Journal Name
Australian Journal Of Basic And Applied Sciences
Block-based Image Steganography for Text Hiding Using YUV Color Model and Secret Key Cryptography Methods
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Publication Date
Fri Jul 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Computer Model Application for Sorting and Grading Citrus Aurantium Using Image Processing and Artificial Neural Network
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Abstract<p>This study was conducted in College of Science \ Computer Science Department \ University of Baghdad to compare between automatic sorting and manual sorting, which is more efficient and accurate, as well as the use of artificial intelligence in automated sorting, which included artificial neural network, image processing, study of external characteristics, defects and impurities and physical characteristics; grading and sorting speed, and fruits weigh. the results shown value of impurities and defects. the highest value of the regression is 0.40 and the error-approximation algorithm has recorded the value 06-1 and weight fruits fruit recorded the highest value and was 138.20 g, Gradin</p> ... Show More
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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Improvement of the monochrome image hologram by using a random phase and increasing number of Samples
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This paper present a study about effect of the random phase and expansion of the scale sampling factors to improve the monochrome image hologram and compared it with previous produced others. Matlab software is used to synthesize and reconstruction hologram.

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Studying the contribution of components and type of spiral galaxy NGC 6946 using digital image processing
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NGC 6946 have been observed with BVRI filters, on October 15-18,
2012, with the Newtonian focus of the 1.88m telescope, Kottamia
observatory, of the National Research Institute of Astronomy and
Geophysics, Egypt (NRIAG), then we combine the BVRI filters to
obtain an astronomical image to the spiral galaxy NGC 6946 which
is regarded main source of information to discover the components of
this galaxy, where galaxies are considered the essential element of
the universe. To know the components of NGC 6946, we studied it
with the Variable Precision Rough Sets technique to determine the
contribution of the Bulge, disk, and arms of NGC 6946 according to
different color in the image. From image we can determined th

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Mon Jul 10 2023
Journal Name
Journal Of Engineering
Removal of Hexavalent Chromium from Aqueous Solutions by Adsorption on Thermally Modified and Non-Modified Eggshells
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Removal of heavy metals from waste water has received a great deal of attention. The compare Cr
(VI) adsorption characteristics removing from wastewater by using thermally modified and non-modified
eggshells were examined

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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Early detection of breast cancer mass lesions by mammogram segmentation images based on texture features
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Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Image And Graphics
DAB-UNET: Dual Attention Block UNET Segmentation for Diabetic Retinopathy Utilizing an Encoder-Decoder Residual
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—Fundus images play an essential role in ophthalmic diagnostics for the detection of many eye illnesses. The experiment begins with a thorough image preprocessing. technique, which includes clipping the circular borders, scaling the image, enhancing the contrast, removing noise, and augmenting the data. The new combined block applies to extracting distinctive deep feature representations, which help to detect the first shape of the edges of each lesion. It is namely the Attention Block and the Conv-Deconv UNET model. The attention block is subsequently implemented in order to augment the robustness and quality of feature depictions derived from a pair of DR images. The Dual Attention Block for the backbone, which is supplement

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