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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
Wed Dec 08 2021
Journal Name
J. Inf. Hiding Multim. Signal Process.
Predication of Most Significant Features in Medical Image by Utilized CNN and Heatmap.

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
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Publication Date
Thu Jul 28 2016
Journal Name
Computer And Information Science
Refinement for Ocular Ultrasound Images Quality by Utilizing Combination of Enhancement Techniques

Ultrasound has been used as a diagnostic modality for many intraocular diseases, due its safety, low cost, real time and wide availability. Unfortunately, ultrasound images suffer from speckle artifact that are tissue dependent. In this work, we will offer a method to reduce speckle noise and improve ultrasound image to raise the human diagnostic performance. This method combined undecimated wavelet transform with a wavelet coefficient mapping function: where UDWT used to eliminate the noise and a wavelet coefficient mapping function used to enhance the contrast of denoised images obtained from the first component. This methods can be used not only as a means for improving visual quality of medical images but also as a preprocessing

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Hybrid Techniques with Support Vector Machine for Improving Artifact Ultrasound Images

     The most common artifacts in ultrasound (US) imaging are reverberation and comet-tail. These are multiple reflection echoing the interface that causing them, and result in ghost echoes in the ultrasound image. A method to reduce these unwanted artifacts using a Otsu thresholding to find region of interest (reflection echoes) and output applied to median filter to remove noise. The developed method significantly reduced the magnitude of the reverberation and comet-tail artifacts. Support Vector Machine (SVM) algorithm is most suitable for hyperplane differentiate. For that, we use image enhancement, extraction of feature, region of interest, Otsu thresholding, and finally classification image datasets to normal or abnormal image.

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Publication Date
Fri Dec 08 2023
Journal Name
Iraqi Journal Of Science
Video Image Compression Using Absolute Moment Block Truncation Method with Orthogonal Search Motion Estimation Technique

Image compression has become one of the most important applications of the image processing field because of the rapid growth in computer power. The corresponding growth in the multimedia market, and the advent of the World Wide Web, which makes the internet easily accessible for everyone. Since the early 1980, digital image sequence processing has been an attractive research area because an image sequence, as acollection of images, may provide much compression than a single image frame. The increased computational complexity and memory space required for image sequence processing, has in fact, becoming more attainable. this research absolute Moment Block Truncation compression technique which is depend on adopting the good points of oth

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Publication Date
Tue May 23 2023
Journal Name
Journal Of Engineering
Numerical Simulation of Ice Melting Using the Finite Volume Method

The Aim of this paper is to investigate numerically the simulation of ice melting in one and two dimension using the cell-centered finite volume method. The mathematical model is based on the heat conduction equation associated with a fixed grid, latent heat source approach. The fully implicit time scheme is selected to represent the time discretization. The ice conductivity is chosen
to be the value of the approximated conductivity at the interface between adjacent ice and water control volumes. The predicted temperature distribution, percentage melt fraction, interface location and its velocity is compared with those obtained from the exact analytical solution. A good agreement is obtained when comparing the numerical results of one

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Publication Date
Thu Mar 02 2023
Journal Name
East European Journal Of Physics
Evaluation of the Influence of Body Mass Index and Signal-to-Noise Ratio on the PET/CT Image Quality in Iraqi Patients with Liver Cancer

Image quality has been estimated and predicted using the signal to noise ratio (SNR). The purpose of this study is to investigate the relationships between body mass index (BMI) and SNR measurements in PET imaging using patient studies with liver cancer. Three groups of 59 patients (24 males and 35 females) were divided according to BMI. After intravenous injection of 0.1 mCi of 18F-FDG per kilogram of body weight, PET emission scans were acquired for (1, 1.5, and 3) min/bed position according to the weight of patient. Because liver is an organ of homogenous metabolism, five region of interest (ROI) were made at the same location, five successive slices of the PET/CT scans to determine the mean uptake (signal) values and its standard deviat

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Publication Date
Tue Apr 01 2014
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Pleural Effusion: Characterization With contrast CT Appearance and CT Attenuation Values

Background: A number of different types of fluid may accumulate in the pleural space, the most common being transudate, exudate (thin or thick), blood and chyle. All types of pleural effusion are radio graphically identical, though historical, clinical and other radiological features may help limit the diagnostic possibilities. Sometimes, also CT and MRI can help to specify the diagnosis.
Objective: To determine the accuracy of computed tomography (CT) in enabling differentiation of pleural exudates from transudates.
Patients and methods: forty three consecutive patients (43 effusions) underwent contrast-enhanced CT. Thoracocentesis was performed to measure pleural and serum total protein values. Effusions were classified as exudat

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Publication Date
Tue Jan 25 2022
Journal Name
Iraqi Journal Of Science
Estimation the best areas of Sun duration hours in Iraq by applying IDW type of interpolation techniques by using GIS program

In this paper solar radiation was studied over the Iraqi countary land. The best sun duration hours regions (maximum hours) in Iraq were estimated detected by using Geographic information system (GIS Ver. 9.2) program to apply the (Inverse distance weighting) IDW exact interpolation technique depending on the measured data of metrological stations were distributed on the land areas of Iraq. The total area of the best regions was calculated .Excel 2007 program is used in calculation, graphics and comparison the results.

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Publication Date
Fri Jul 01 2016
Journal Name
International Journal Of Computer Science And Mobile Computing