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Estimation of kidney tumor volume in CT images using medical image segmentation techniques

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
Sat Dec 31 2022
Journal Name
Al-kindy College Medical Journal
Pulmonary CT findings in Patients Recovered from COVID-19 Pneumonia

Background: The COVID-19 infection is a more recent pandemic disease all over the world and studying the pulmonary findings on survivors of this disease has lately commenced.

Objective: We aimed to estimate the cumulative percentage of whole radiological resolution after 3 months from recovery and to define the residual chest CT findings and exploring the relevant affecting factors.

Subjects and Methods: Patients who had been previously diagnosed with COVID-19 pneumonia confirmed by RT-PCR test and had radiological evidence of pulmonary involvement by Chest CT during the acute illness were included in the present study. The radiol

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Publication Date
Sun Apr 01 2007
Journal Name
Journal Of The Faculty Of Medicine Baghdad
CT Evaluation of Liver Hydatid Disease

Background: To elucidate distinctive CT imaging features that allows a diagnosis of hepatic hydatidosis.
Patients and methods : The computed tomographic (CT) findings of 58 patients with sonographically detected cystic liver lesions were prospectively analyzed. These patients were
followed up until a final diagnosis was reached.
Results : By CT scanning we correctly localized and diagnosed 81 hepatic hydatid cysts in 50 patients. These were all proved by surgery or endoscopic retrograde cholangio-pancreatography (ERCP). Stage III and II hydatid cysts were the commonest types (29 % and 25 % respectively ). 52 % of the cysts were 5-10 cm at presentation. At CT, we identified some ancillary imaging fea

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Clouds Height Classification Using Texture Analysis of Meteosat Images

In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

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Publication Date
Sun Apr 01 2007
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Aflatoxin B1-Induced Kidney Damage in Rats

Background: Aflatoxin B1 (AFB1) is a widely distributed mycotoxin in nature. Several investigations have shown its biological effects on different organs and in different animal species. However, the effects of AFB1 on the rat kidney have not been much elucidated histologically.
Objective: This study aims to demonstrate the effects of AFB1 contaminated diet on the rat kidney from
the histological and morphometric aspects.
Method: Twelve mature albino rats were divided equally into a control group fed with usual diet and a treated group which was daily fed with diet contaminated with 20 mg AFB1/kg of body weight for 30 days. Semithin sections from renal cortex were stained with methylene blue and examined by l

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of The College Of Basic Education
Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Science
A Study of Desertification Using Remote Sensing Techniques in Basra Governorate, South Iraq

Iraq territory as a whole and south of Iraq in particular encountered rapid desertification and signs of severe land degradation in the last decades. Both natural and anthropogenic factors are responsible for the extent of desertification. Remote sensing data and image analysis tools were employed to identify, detect, and monitor desertification in Basra governorate. Different remote sensing indicators and image indices were applied in order to better identify the desertification development in the study area, including the Normalized difference vegetation index (NDVI), Normalized Difference Water Index (NDWI), Salinity index (SI), Top Soil Grain Size Index (GSI) , Land Surface Temperature (LST) , Land Surface Soil Moisture (LSM), and La

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Publication Date
Mon May 01 2023
Journal Name
Journal Of Economics And Administrative Sciences (jeas)
Using Statistical Methods to Increase the Contrast Level in Digital Images

This research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods

Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Science
Auto Colorization of Gray-Scale Image Using YCbCr Color Space

The process of converting gray images or videos to color ones by adding colors to them and transforming them from one-dimension to three-dimension is called colorization. This process is often used to make the image appear more visually appealing. The main problem with the colorization process is the lack of knowledge of the true colors of the objects in the picture when it is captured. For that, there is no a unique solution. In the current work, the colorization of gray images is proposed based on the utilization of the YCbCr color space. Reference image (color image) is selected for transferring the color to a gray image. Both color and gray images are transferred to YCbCr color space. Then, the Y value of the gray image is combined w

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Publication Date
Thu Jun 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Satellite Images Fusion Using Modified PCA Substitution Method

In this paper, a new tunable approach for fusion the satellite images that fall in different electromagnetic wave ranges is presented, which gives us the ability to make one of the images features little superior on the other without reducing the general resultant image fusion quality, this approach is based on the principal component analysis (PCA) fusion method. A comparison made is between the results of the proposed approach and two fusion methods (they are: the PCA fusion method and the projection of eigenvectors on the bands fusion method), and the comparison results show the validity of this new method.

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