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29 results for “Automated Diagnosis”
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Research ArticleOpen accessIn the abstractCrop Disease Detection Using Deep Learning Techniques on ImagesKinjal Vijaybhai Deputy, Kalpdrum Passi, Chakresh Kumar JainAgriculture plays a crucial role in the economic development of many countries and sustains the global population despite facing various challenges like climate change, pollinator decline, and plant diseases. These threats to food security highlight the need for innovative solutions to prevent crop loss. Leveraging smartphone technology for automated image recognition-based disease diagnosis has emerged as a promising approach, thanks … …Journal of Computer Science, Vol. 19, Issue 12 · 25 Oct 2023 · 7,497 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comprehensive Review on Skin Cancer Detection Strategies using Deep Neural NetworksAkepati Sankar Reddy, Gopinath M. PSkincancer is a deadly malignancy. Incomplete D.N.A. repair in skin cells causeshereditary mutations and cancer. Early skin cancer is easier to treat since itspreads slowly to other body areas. As a result, the optimal time to find it isduring its infancy. Because of the rising frequency of skin cancer, the highmortality rate, and the high cost of medical treatment, early … …Journal of Computer Science, Vol. 18, Issue 10 · 5 Oct 2022 · 6,400 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiagnosing Alzheimer’s Disease using Convolution Neural NetworksSarita, Saurabh Mukherjee, Tanupriya Choudhury et al.Alzheimer’s is a disease wherein constant degeneration of neurons and their synapses result in impaired brain functioning which leads to personality changes, memory loss, thinking and speech disorder. So, there is a requirement of an automated and early diagnosis of this disease to decrease the death rate. The proposed work is coupled with deep learning techniques to predict the Alzheimer’s … …Journal of Computer Science, Vol. 18, Issue 2 · 21 Feb 2022 · 7,344 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Survey of Graph Based Complex Brain Network Analysis Using Functional and Diffusional MRIMd Rafiqul Islam, Xiaoxia Yin, Anwaar Ulhaq et al.The brain network is the function of a structurally and functionally organized complex system. Its structure and activity analysis is one of the most significant challenges. The graph based techniques of brain complex networks have been successfully used in various types of image and medical data analysis. In this survey paper, we focus on a comprehensive study of the analytical … …American Journal of Applied Sciences, Vol. 14, Issue 12 · 8 Jan 2018 · 9,249 accessesView PDFCite
Research ArticleOpen accessIn the abstractExtracting the Potential Features of Digital Panoramic Radiograph Images by Combining Radio Morphometry Index, Texture Analysis, and Morphological FeaturesEnny Itje Sela, SutarmanOsteoporosis is a type of disease that is not easily detected visually. It contributes to bone fracture and so early diagnosis is particularly important to prevent bone fracture. An integrated approach for extraction of cortical and trabecular bone on the digital panoramic radiograph (DPR) images was proposed to screen osteoporosis. We performed radio morphometry index (RMI), texture analysis, and morphology … …Journal of Computer Science, Vol. 14, Issue 2 · 7 Dec 2017 · 8,026 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Four-Directional Thresholding Approach for Lung Computed-Tomography Images by Using Similarity-Based Segmentation TechniqueSaleheh Heidari, Muhamad Taufik Abdullah, Lili Nurliana AbdullahIn automated pulmonary nodules extraction and lung disease diagnosis by image processing techniques, image segmentation is utilized as a primary and the most essential step of lung tumor analysis. But due to extensive similarity between pulmonary vessels, bronchus and arteries in lung region and the low contrast of the Computed-Tomography (CT) image the accuracy of lung tumor diagnosis is highly … …Journal of Computer Science, Vol. 11, Issue 1 · 17 Sep 2014 · 7,477 accessesView PDFCite
Research ArticleOpen accessIn the abstractPERFORMANCE ANALYSIS OF BRAIN TUMOR DIAGNOSIS BASED ON SOFT COMPUTING TECHNIQUESP. Shantha Kumar, P. Ganesh KumarComputed tomography images are widely used in the diagnosis of brain tumor because of its faster processing, avoiding malfunctions and suitability with physician and radiologist. This study proposes a new approach to automated detection of brain tumor. This proposed work consists of various stages in their diagnosis processing such as preprocessing, anisotropic diffusion, feature extraction and classification. The local binary … …American Journal of Applied Sciences, Vol. 11, Issue 2 · 27 Dec 2013 · 6,985 accessesView PDFCite
Research ArticleOpen accessIn the abstractBLOOD VESSELS EXTRACTION USING MATHEMATICAL MORPHOLOGYNidhal Khdhair El Abbadi, Enas Hamood Al SaadiThe retinal vasculature is composed of the arteries and veins with their tributaries which are visible within the retinal image. The segmentation and measurement of the retinal vasculature is of primary interest in the diagnosis and treatment of a number of systemic and ophthalmologic conditions. The accurate segmentation of the retinal blood vessels is often an essential prerequisite step in … …Journal of Computer Science, Vol. 9, Issue 10 · 12 Sep 2013 · 7,095 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing Feature Selection as Accuracy Benchmarking in Clinical Data MiningJafreen Hossain, Nor FazlidaMohdSani, Aida Mustapha, Lilly SurianiAffendeyAutomated prediction of new patients’ disease diagnosis based on data mining analysis on historical data is proven to be an extremely useful tool in the medical innovation. There are several studies focusing on this particular aspect. The objective of this study is two-fold. First, we look into three different classifiers, which are the Naïve Bayes, Multilayer Perceptron (MLP) and Decision … …Journal of Computer Science, Vol. 9, Issue 7 · 20 Jun 2013 · 7,460 accessesView PDFCite
Research ArticleOpen accessIn the abstractSegmentation of Ureteric and Bladder Calculi in Ultrasound ImagesS. SridharProblem statement: The framework for segmenting calculi in ureter and bladder using ultrasound images is proposed in this study. Calculi are due to abnormal collection of certain chemicals like oxalate, phosphate and uric acid. These calculi can be present in kidney, urethra or in urinary bladder. The extraction of calculi in medical images is a difficult task as no standard … …Journal of Computer Science, Vol. 8, Issue 5 · 27 Feb 2012 · 6,917 accessesView PDFCite