Journal of Physics Conference Series · 2021 · 22 citations · 10 references
MedicineInfectious DiseasesRadiologyComputer VisionDiagnostic ImagingDiagnostic RadiologyComputed TomographyComputer-aided DiagnosisMedical Image AnalysisMedical ImagingPulmonary InfectionsRespiratory InfectionsDeep Learning In RadiologyHybrid Imaging In InfectionLung Infection ImagingMulti-slice Computed TomographyX-ray Computed Tomography
Abstract Lung infection or sickness is one of the most common acute ailments in humans. Pneumonia is one of the most common lung infections, and the annual global mortality rate from untreated pneumonia is increasing. Because of its rapid spread, pneumonia caused by the Coronavirus Disease (COVID-19) has emerged as a global danger as of December 2019. At the clinical level, the COVID-19 is frequently measured using a Computed Tomography Scan Slice (CTS) or a Chest X-ray. The goal of this study is to develop an image processing method for analyzing COVID-19 infection in CTS patients. The images in this study were preprocessed using the Hybrid Swarm Intelligence and Fuzzy DPSO algorithms. The findings suggest that the proposed method is more dependable, accurate, and simple than existing methods.
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Ophir Gozes, Maayan Frid-Adar, Hayit Greenspan et al. · arXiv (Cornell University) · 2020 · 672 citations · Full text
Veterinary Medicine, Health Informatics, Infectious Diseases +17
Weakly Supervised Deep Learning for COVID-19 Infection Detection and Classification From CT Images
Shaoping Hu, Yuan Gao, Zhangming Niu et al. · IEEE Access · 2020 · 402 citations · Full text
Coronavirus Detection and Analysis on Chest CT with Deep Learning
Ophir Gozes, Maayan Frid-Adar, Nimrod Sagie et al. · arXiv (Cornell University) · 2020 · 104 citations · Full text