Studying the effect of cold plasma on the blood using digital image processing and images texture analysis

Mazhir, Sabah N.; Ali, Alyaa H.; Abdalameer, Nisreen Kh.

doi:10.1109/scopes.2016.7955574

Cited by 7 publications

(10 citation statements)

References 9 publications

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“…It depends on grouping the intensity according to the threshold value, it can remove the object from the context. The resulting image for one threshold as calculated by 11 g(x, y…”

Section: Methodsmentioning

confidence: 99%

Influence of Cold Plasma on Sesame Paste and the Nano Sesame Paste Based on Co-occurrence Matrix

et al. 2022

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The aim of the research is to investigate the effect of cold plasma on the bacteria grown on texture of sesame paste in its normal particle and nano particle size. Starting by using the image segmentation process depending on the threshold method, it is used to get rid of the reflection of the glass slides on which the sesame samples are placed. The classification process implemented to separate the sesame paste texture from normal and abnormal texture. The abnormal texture appears when the bacteria has been grown on the sesame paste after being left for two days in the air, unsupervised k-mean classification process used to classify the infected region, the normal region and the treated region. The bacteria treated with cold plasma, the time exposure is two minutes. The textural features related to gray level co-occurrence matrix are calculated for the normal, abnormal and the treated texture, it is obvious that the treated texture class has the best features compared with the other classes. The result shows the sesame paste treated with plasma has good result compared with nano sesame paste treated with plasma. This is because the plasma provides the sesame paste with heat and makes the sesame nano particle congregate together.

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“…It depends on grouping the intensity according to the threshold value, it can remove the object from the context. The resulting image for one threshold as calculated by 11 g(x, y…”

Section: Methodsmentioning

confidence: 99%

Influence of Cold Plasma on Sesame Paste and the Nano Sesame Paste Based on Co-occurrence Matrix

et al. 2022

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“…Histogram equalization (HE) is one of the most typical contrast enhancement techniques. The main idea behind HE is to map the gray levels with a narrow range to the gray levels with a wide range [13]. However, HE is not suitable for images with a large difference between background and foreground, as Fig.…”

Section: B Image Enhancementmentioning

confidence: 99%

“…The Laplacian operator is represented by equation 11, and the LOG filter is described by equation 12[20], while filter(i,j) denotes the value in the filter at the position (i,j) [16]. Further, the intensity-based features are extracted from the output images, and the output image is defined by equation (13), where f means the input image, g denotes the output image, filter represents the LOG filter and * stands for the operation of convolution.…”

Section: Skementioning

confidence: 99%

A Noninvasive System for the Automatic Detection of Gliomas Based on Hybrid Features and PSO-KSVM

et al. 2019

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Due to their location, malignant brain tumors are one of humanity's greatest killers, among these tumors, gliomas are the most common. The early detection of gliomas can contribute to the design of proper treatment schemes and, thus, improve the survival rate of patients. However, it is a challenging task to detect the gliomas within the complex structure of the brain. The conventional artificial diagnosis is timeconsuming and relies on the clinical experience of radiologists. To detect gliomas more efficiently, this paper proposes a noninvasive automatic diagnosis system for gliomas based on the machine learning methods. First, image standardization, including size normalization and background removal, is applied to produce standard images; then, the modified dynamic histogram equalization is implemented to enhance the low-contrast standard brain images, and skull removal based on outlier detection is presented. Furthermore, hybrid features, including gray-level co-occurrence matrix, pyramid histogram of the oriented gradient, modified completed local binary pattern, and intensity-based features are extracted together from the enhanced images, and their dimensions are reduced by principal component analysis. Kernel support vector machine (KSVM) combined with the particle swarm optimization is eventually adopted to train classifiers; in this paper, brain magnetic resonance imaging images are labeled with normal, glioma, and other. The experimental results show that the accuracy, sensitivity, and specificity of the proposed method can reach 98.36%, 99.17%, and 97.83%, respectively, which indicates that the proposed method performs better than many current systems. INDEX TERMS Modified CLBP, PSO-KSVM, Glioma detection, hybrid features, skull removal. FIGURE 3. The process of background removal based on an adaptive threshold.

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“…First order statistical parameters are computed from the image intensity values without bearing in mind the pixel neighbor connection. [22] 1-mean and the standard deviation:-utilized to measure the prevalence of gray level values of the pixels within that region (Histogram). [23] 2-Variance:-is a measure of the histogram width that measures the aberration of gray levels from the Mean [23] 3-skewness and kurtosis:-skewness indicates a measure of the degree of histogram asymmetry around the mean, and kurtosis measure the sharpness of histogram.…”

Section: First-order Statisticsmentioning

confidence: 99%

Studying the effect of Dielectric Barrier Discharges on the Leukemia Blood Cells Using Digital Image Processing

Mazhir¹,

Ali²,

Hadi³

et al. 2017

IOSRJPBS

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Studying the effect of cold plasma on the blood using digital image processing and images texture analysis

Cited by 7 publications

References 9 publications

Influence of Cold Plasma on Sesame Paste and the Nano Sesame Paste Based on Co-occurrence Matrix

Influence of Cold Plasma on Sesame Paste and the Nano Sesame Paste Based on Co-occurrence Matrix

A Noninvasive System for the Automatic Detection of Gliomas Based on Hybrid Features and PSO-KSVM

Studying the effect of Dielectric Barrier Discharges on the Leukemia Blood Cells Using Digital Image Processing

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