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Detection of Anemia Disease Using Pso Algorithm and Lbp Texture Analysis

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Detection of Anemia Disease Using Pso Algorithm and Lbp Texture Analysis International Journal of Pure and Applied Mathematics Volume 120 No. 6 2018, 15-26 ISSN: 1314-3395 (on-line version) url: http://www.acadpubl.eu/hub/ Special Issue http://www.acadpubl.eu/hub/ DETECTION OF ANEMIA DISEASE USING PSO ALGORITHM AND LBP TEXTURE ANALYSIS 1S. Dhanasekaran M.E., 2Dr. N. R. Shanker Ph.D., 1Research Scholar, 2Professor/ Supervisor-Aalim Muhammed Salegh College of Engineering Department of Electronics and Communication Engineering PRIST University, Thanjavur, Tamilnadu Abstract: Nowadays, patients with anemia disease oxygen from the lungs to different parts of the body and present in the world increased by around 60-70% also to carrying maximum carbon dioxide (CO2) from respectively. The digital image processing technique has different parts of the body to lungs. successfully characterised to introduce new methods for Functional near-infrared spectroscopy (fNIRS) is disease analysis has lead to reliable systems and more utilised to differentiatethe patient with schizophrenia, and accurate for anemia disease diagnosis. This paper gives the healthy persons are based on the support vector an algorithm for the automatic detection of anemia machine (SVM) and principal component analysis disease through palm image. For solving such issues, a (PCA). Firstly, PCA is utilized to select the features on PSO algorithm and LBP texture analysis are applied for oxygenated haemoglobin (oxy-Hb) signals from the classification of palm images. There are several features different channel fNIRS data. Secondly, aextraction is are consider based on statistical analysis, i.e. mean, based on SVM is planned to separate the schizophrenia variance and entropy have been extracted. The from a healthy people. Finally, the method gives an classification results demonstrate that these features accuracy of 93.33%, 84.62% for healthy people and highly import and can be utilised to identify normal and 100% for schizophrenia. AfNIRSmethod hasa potential abnormal patients 98% successfully. capacity and an effective aim biomarker for the analysis of schizophrenia [1]. Keyword: Digital image processing, Anemia disease Leukaemia patient’s presents with reduced diagnosis, PSO Algorithm and LBP Texture analysis. haemoglobin and the WBC count in about 60-70% of cases. Peripheral blood smear (PBS) method brings out 1. Introduction about 40-95% of blast cells in leukaemia patients. The digital image processing method has successfully lead to Anemia is a disease, due to the lack of the total amount developing new techniques for cell diagnosis has lead to of haemoglobin or red blood cells (RBCs) in the blood, more reliable and accurate systems for disease analysis. or a brought capacity of the blood down to carry However, high differences in cell size, edge, shape and oxygen.Red blood cells (are also called as erythrocytes) localisation make more complex the data extraction are the most basic type of blood cell, and the vertebrate process. The electromagnetism-like optimisation (EMO) organism’s principal entails of delivering oxygen (O2) to algorithm introduced to detect automatically white blood the body tissues via the blood flow by the circulatory cells embedded into intricate smear an image that takes system. They absorb oxygen in the gills or lungs and the total function as a circle detection problem. The EMO release it while forcing by the body’s capillaries. technique gives a result from blood cell images with a Haemoglobin (Hb) is a blood content containing protein changing range of complication are admitted to formalise and iron. The human beings become unhealthy while Hb the efficiency concerning detection, stability and ranges in their blood level are reduced to a certain fixed robustness[2]. limit as for females is 11 mg/dL and for males is 13 Blood cell categorisation is the beginning process for mg/dL.There are different stages of this health problem finding disease; the diseases can be contained if it is and are consequently called severe anemia, moderate detected at the starting stage. To solve problems, anemia and mild anemia. The decrease in Hb level in quantitative processing of digital images based on a fuzzy blood is because of the deficiency of folic acid, vitamin method is introduced for categorisation of red blood B12, or iron. Nowadays, anemia occurs due to the cells. There are different features consist of size, shape deficiency of iron is normally very common. So, a and colour based features, that based on statistical decrease in the iron level will outcome in decreased analysis (i.e. kurtosis, roundness, skewness, mean, oxygen carrying capacity of the blood, which can hurt the variance, standard deviation) have been extracted. The health of people. In blood, Hb is worthy of carrying categorisation results showed that features significance 15 International Journal of Pure and Applied Mathematics Special Issue highly and can be utilised for categorisation of red cells uncertainties, and then we can extract the to the normal and up normal cells. The result presents a knowledgeabout the component which creates diabetes. 98% of red blood cells successfully[3]. From the analysis, BMI will be the biggest influencer Anemic status in children and women all over the about HbAlc changes. The first step for maintaining the world area important things for concern. In human blood, health is the daily monitoring. A MEMS-based small and haemoglobin is measured by a standard technique is adaptable monitoring devicehas been created by the cyanmethemoglobinand the world health organisation ERATO maenaka human-sensing fusion design. We (WHO) is also recommended as a well-recognised developed a condition estimation strategy utilising the method. While comparing to this method, there are monitoring device and FNN-based condition estimation. several methods available with an approximate result. The experiment results demonstrate that it is a promising One among the method is colour-measurement technique, strategy for health condition understanding. One of the and in low resource settings adaptation, the WHO important lifestyle diseases iscerebral vascular and is recommended this technique.Human interpretation errors caused by cerebral aneurysms. To detect the disease in are probably moved slowly in during the subjective the forecast, we should analyse aneurysms and cerebral process required with this colour-measurement technique, arteries utilising magnetic resonance angiography images in human blood Hb count is measured by an artificial [6]. neural network (ANN) method. The ANN utilised input A novel technique is utilised to extract haemoglobin as the Hb value and the colour-coded values of the and melanin centralisations of human skin, utilising samples, as received with the cyanmethemoglobin bilateral decomposition with the information of a technique, as trusted output. The results demonstrate a numerous layered skin model and absorbance attributes warm relation among the Hb level in the blood and the of major chromophores. The proposed method is colour of the blood sample [4]. different from the state-of-art method, is to address the Thalassemia is an inherent issue of haemoglobin feature and strong shadinggenerally in existing systems blend, which can lead to stroke in the brain and the skin colour images are caught under the uncontrolled thromboembolic case. In this work, utilising a functional conditions. The determined haemoglobin and melanin connectivity model to separate amongst diseased subject files, specifically identified with the pathological tissue and control. Our connectivity measure depends on conditions, tend to be less impacted by external imaging functional magnetic resonance imaging, and hence the factors and are efficient in distinguishing pigmentation regular changes of the blood oxygenation level in distributions. Experiments show the estimation of the spatially removed areas. Examining this connectivity proposed technique for computer-aided analyses of could feature unusual neuronal activation and give us a various skin diseases. The analyses exactness of descriptor (bio-marker) of the infection. To estimate the melanoma raises by 9-15% for conventional RGB lesion connectivity, developed a robust learning method in light images, equated to the techniques utilised early colour of the graphical lasso model, whose hyperparameter is descriptors. The of hyperpigmentation reveals acne and approved inside a cross-validation scheme. To examine inflammatory acne stage, which would be utilised for model fit, we exchange the mean property from the acne severity valuation[7]. control group to the thalassemic patient group. Null Basal cell carcinoma (BCC) is the mostbasic type of hypothesis model is learned from control subjects, and it skin cancer. Analysis of BCC is an essential factor in the is equally suitable ( in the likelihood sense) to explain to forecast of the disease.The vascular structures of the the patients. The permutation test results give that the few lesion are the important key for BCC analysis. Discovery patients with thalassemia do not have the same and realisation of cutaneous vasculature give basic data connectivity structure as the control[5]. on the determination of exactness and evaluation To predict and prevent the lifestyle disease utilising accuracy. An effective method is demonstrated to daily monitoring the health, periodical health checkup separate vascular data towards lesion analysis. Given a and detection through medical imaging. Here, three new dermoscopy image, initially vascular structures
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