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18 articles for “Lung CT Image”

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Research ArticleOpen accessIn the abstractA Robust Ensemble Convolutional Neural Networks for Diagnosing Chest DiseasesMansour Ali Alhlalat, Ahmad Abdel-Aziz Sharieh, Mohammed Belal Al-ZoubiRadiologists employ X-ray images to differentiate various chest diseases. Given the intricate and meticulous nature of this diagnostic procedure, the assistance of automated models becomes imperative in detecting and diagnosing diseases from X-ray images. This research paper proposed a novel approach called Ensemble Convolutional Neural Network for Diagnosing Chest Diseases (ECDCNet), aimed at accurately and efficiently diagnosing fifteen different chest … …Journal of Computer Science, Vol. 19, Issue 12 · 27 Oct 2023 · 5,104 accessesView PDFCite
Research ArticleOpen accessIn the abstractTransfer Learning-Driven Binary Classification of Chest X-ray for Pneumonia Using Deep Convolutional ArchitecturesNusrath Fathima, Pradeep KumarPneumonia is the most common infectious cause of lung inflammation, resulting from the presence of viruses or bacteria in the microscopic air sacs. In recent years, artificial intelligence, particularly deep learning, has gained significant traction in the field of medical imaging. Early detection and diagnosis of pneumonia using chest X-rays can support radiologists in clinical decision-making and subsequent treatment planning, … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,542 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetection of Pulmonary Nodules in ct Images Using Deep Learning TechniqueSanthi Balachandran, Divya, Nithya Rajendran, Brindha GiriLung Cancer is one of the most deadly diseases worldwide. According to the American Cancer Society, about 234,030 peoples have been suffering from lung cancer. It can be cured if it is diagnosed earlier which decreases the death rate. A computational diagnostic tool named Computer Aided Diagnosis (CAD) is used to detect pulmonary nodules. Extensive work has been made in … …Journal of Computer Science, Vol. 16, Issue 4 · 15 Apr 2020 · 7,816 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn 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 abstractMiliary Tuberculosis: A Case ReportZhinous Bayat Makoo, Roshanak Bayat Makoo, Omid MashrabiProblem statement: During the last years it is more than evident that the prevalence of pulmonary and extrapulmonary Tuberculosis (TB), mainly in western European countries, has risen significantly. The aetiology of this phenomenon is multifactorial. Miliary tuberculosis is a form of tuberculosis that is characterized by millet-like seeding of TB bacilli in the lung, as evidenced on chest radiography. Approach: … …American Journal of Infectious Diseases, Vol. 6, Issue 4 · 31 Dec 2010 · 7,623 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Computer Aided Diagnosis System for Lung Cancer Detection\Using Support Vector MachineM. Gomathi, P. ThangarajProblem statement: Computer Tomography (CT) has been considered as the most sensitive imaging technique for early detection of lung cancer. Approach: On the other hand, there is a requirement for automated methodology to make use of large amount of data obtained CT images. Computer Aided Diagnosis (CAD) can be used efficiently for early detection of Lung Cancer. Results: The usage … …American Journal of Applied Sciences, Vol. 7, Issue 12 · 31 Dec 2010 · 8,285 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Technique to Detect the Region of Interests in Mammogram ImagesMoussa H. Abdallah, Ayman A. AbuBaker, Rami S. Qahwaji, Mohammed H. SalehProblem Statement: Breast cancer is the second leading cause of cancer deaths in women today after lung cancer and is the most common cancer among women. The development of efficient technique to early detect the region of microcalcifications mammogram images is a must. Approach: The method proposed in this paper is to enhance the Computer Aided Diagnosis (CAD) performance. This … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 6,629 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordLung Cancer Detection Using Regularized Extreme Learning Machine and PCA FeaturesK. Kavitha, Dr. V. Saravana Kumar, V. Bhoopathy et al.When finding abnormalities in target images is time-sensitive, as it is with many cancer tumors, image processing techniques have recently found widespread use across various medical industries to improve images for early detection and treatment stages. In the setting of cancer, where time is of the essence in detecting anomalies within medical imaging, our research takes on further urgency. In … …Journal of Computer Science, Vol. 20, Issue 10 · 5 Aug 2024 · 5,302 accessesView PDFCite