Wenqian Li¹, Xing Deng^1,2,*, Haijian Shao¹, Xia Wang³

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 65-98, 2021, DOI:10.32604/cmes.2021.016981

Abstract The COVID-19 has resulted in catastrophic situation and the deaths of millions of people all over the world. In this paper, the predictions of epidemiological propagation models, such as SIR and SEIR, are introduced to analyze the earlier COVID-19 propagation. The deep learning methods combined with transfer learning are familiar with classification-detection approaches based on chest X-ray and CT images are presented in detail. Besides, deep learning approaches have also been applied to lung ultrasound (LUS), which has been shown to be more sensitive than chest X-ray and CT images in detecting COVID-19. In the absence of a vaccine, the… More > Graphic Abstract

Muhammad Arslan Usman^1,4,*, Muhammad Rehan Usman², Rizwan Ali Naqvi³, Bernie Mcphilips⁴, Christopher Romeika⁴, Daniel Cunliffe⁴, Christos Politis¹, Nada Philip¹

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 529-547, 2021, DOI:10.32604/cmc.2021.014614

Abstract Video compression in medical video streaming is one of the key technologies associated with mobile healthcare. Seamless delivery of medical video streams over a resource constrained network emphasizes the need of a video codec that requires minimum bitrates and maintains high perceptual quality. This paper presents a comparative study between High Efficiency Video Coding (HEVC) and its potential successor Versatile Video Coding (VVC) in the context of healthcare. A large-scale subjective experiment comprising of twenty-four non-expert participants is presented for eight different test conditions in Full High Definition (FHD) videos. The presented analysis highlights the impact of compression artefacts on… More >