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31 results for “Computer-Aided Diagnosis”
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Research ArticleOpen accessIn the keywordsRadial Basis Function Networks and Contrast-Limited Adaptive Histogram Equalization Filter Based Early-Stage Breast Cancer Detection TechniquesAnitha Ponraj, Aroul CanessaneBreast cancer is one of the most common types of cancer that kills women. When cells become uncontrollably large, cancer develops. As a result, detecting and classifying breast cancer in its early stages is essential so that patients can take the appropriate precautions. On the other hand, mammography images have relatively low sensitivity and effectiveness in detecting breast cancer. Furthermore, … …Journal of Computer Science, Vol. 19, Issue 6 · 25 May 2023 · 5,613 accessesView PDFCite
Research ArticleOpen accessIn the keywordsClassification of Normal and Abnormal Lung CT-scan Images Using Cellular Learning AutomataNooshin Hadavi, Md Jan Nordin, Ali Shojaeipour, Mohammad Faidzul NasrudinThis paper proposes a medical pattern recognition system based on the Cellular automata (CA). CA or cellular machine is a dynamic mathematical model that consists of several similar and simple units organized by considerably simple local rules. Each cell acts as a simple computer automaton. This can lead to the implementation of the complex computations through uncomplicated methods. However, the … …Journal of Computer Science, Vol. 16, Issue 1 · 15 Jan 2020 · 7,834 accessesView PDFCite
Literature ReviewOpen accessIn the keywordsA Comprehensive Survey on Tools for Effective Alzheimer’s Disease DetectionN. Vinutha, G. U. Vasanthakumar, P. Deepa Shenoy, K. R. VenugopalNeuroimaging is considered as a valuable technique to study the structure and function of the human brain. Rapid advancement in medical imaging technologies has contributed significantly towards the development of neuroimaging tools. These tools focus on extracting and enhancing the relevant information from brain images, which facilitates neuroimaging experts to make better and quick decision for diagnosing enormous number of … …Neuroscience International, Vol. 9, Issue 1 · 4 Oct 2017 · 10,232 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Adaptive Region Growing Algorithm with Support Vector Machine Classifier for Tuberculosis Cavity IdentificationK. Meenakshi Sundaram, C. S. RavichandranThe major world health menace is Tuberculosis (TB) that has the effect on one-third of the global population and millions of new infections are occurring every year. The cavities in the upper lung zone are a strong indicator that the disease has developed into a highly contagious state. The study includes 52 Chest X-ray images with Tuberculosis and 43 Chest … …American Journal of Applied Sciences, Vol. 10, Issue 12 · 29 Oct 2013 · 7,067 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAdaptive Neuro-Fuzzy Inference System Approach for the Automatic Screening of Diabetic Retinopathy in Fundus ImagesS. Kavitha, K. DuraiswamyProblem statement: Diabetic retinopathy is one of the most significant factors contributing to blindness and so early diagnosis and timely treatment is particularly important to prevent visual loss. Approach: An integrated approach for extraction of blood vessels and exudates detection was proposed to screen diabetic retinopathy. An automated classifier was developed based on Adaptive Neuro-Fuzzy Inference System (ANFIS) to differentiate … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 6,785 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPsoriasis Detection Using Skin Color and Texture FeaturesNidhal K. El Abbadi, Nizar Saadi Dahir, Muhsin A. AL-Dhalimi, Hind RestomProblem statement: In this study a skin disease diagnosis system was developed and tested. The system was used for diagnosis of psoriases skin disease. Approach: Present study relied on both skin color and texture features (features derives from the GLCM) to give a better and more efficient recognition accuracy of skin diseases. We used feed forward neural networks to classify … …Journal of Computer Science, Vol. 6, Issue 6 · 30 Jun 2010 · 8,290 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Wavelet, Curvelet, and Contourlet Transforms for Denoising Liver CT ImagesMajzoob Kamalaldin Omer AbdalrahmanLiver cancer is one of the leading causes of mortality worldwide, and early detection using CT imaging plays a critical role in patient survival. However, the quality of CT scans is often degraded by noise, particularly in low-dose imaging intended to minimize radiation exposure. This study presents a comprehensive comparison of three multiresolution transform techniques, namely the wavelet, curvelet, and … …Journal of Computer Science, Vol. 22, Issue 1 · 4 Feb 2026 · 2,117 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Thoracic X-Ray Images of COVID-19 Patients Using the Convolutional Neutral Network (CNN) MethodRamacos Fardela, Dian Milvita, Mawanda Almuhayar et al.Recently, radiology modalities have been widely used to detect COVID-19. Thoracic X-rays and CT scans are the primary radiological tools utilized in the diagnosis and treatment of individuals with COVID-19. In addition, chest CT scans are more accurate and sensitive in early COVID-19 identification. A new problem arises in diagnosing the results of CT scan images of COVID-19 by radiologists … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 5,753 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage-Based Alzheimer's Disease Detection Using Pretrained Convolutional Neural Network ModelsNasser AlsadhanAlzheimer's disease is an untreatable, progressive brain disorder that slowly robs people of their memory, thinking abilities, and ultimately their capacity to complete even the most basic tasks. Among older adults, it is the most frequent cause of dementia. Although there is presently no treatment for Alzheimer's disease, scientific trials are ongoing to discover drugs to combat the condition. Treatments … …Journal of Computer Science, Vol. 19, Issue 7 · 28 Jun 2023 · 5,909 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiagnosis of Cardiovascular Diseases with Bayesian ClassifiersAlaa Elsayad, Mahmoud FakhrCardiovascular disease or atherosclerosis is any disease affecting the cardiovascular system. They include coronary heart disease, raised blood pressure, cerebrovascular disease, peripheral artery disease, rheumatic heart disease, congenital heart disease and heart failure. They are treated by cardiologists, thoracic surgeons, vascular surgeons, neurologists and interventional radiologists. The diagnosis is an important yet complicated task that needs to be done accurately … …Journal of Computer Science, Vol. 11, Issue 2 · 25 Mar 2015 · 7,498 accessesView PDFCite