Author Archives: azaleaazelia
Imaging in coronavirus disease 2019 part 4
The virus outbreak presumably originated via a zoonotic transmission linked to the seafood market in Wuhan (China) and later accelarated with human to human transmission, causing the severe subsequent outbreak. Since the original outbreak, SARS-CoV2 has rapidly spread across the … Continue reading
Imaging in coronavirus disease 2019 part 3
In late November 2019, a serious form of pulmonary illness originated in Wuhan City (Hubei province, China) an engulfed a majority of the world. This pneumonia outbreak was attributed to a novel coronavirus, a lipid-enveloped RNA virus, which was named … Continue reading
Imaging in coronavirus disease 2019 part 2
The limitations of RT-PCR, specifically. the fact that it is time-consuming and inadequate for the assessment of disease severity, have affected the process of epidemiological disease containment and has taken a toll on the healthcare management chain. As the risk … Continue reading
Imaging in coronavirus disease 2019 part 1
Coronavirus disease-2019 (COVID-19) originated in the Wuhan, Hubei Province, China in November 2019 and has since been declared a pandemic by the WHO. COVID-19 is an acute infectious disease, primarily affecting the respiratory system. Currently, real-time reverse transcription polymerase chain … Continue reading
Imaging of coronavirus disease 2019 part 26
In general, combined chest CT, clinical symptoms, and laboratory tests facilitates the diagnosis of COVID-19. Increasing in-depth understanding of the disease, research, and the continuous improvement of artificial intelligence technology will further promote the establishment of a comprehensive prevention and … Continue reading
Imaging of coronavirus disease 2019 part 25
Some researchers have tried to apply artificial intelligence in CT image analysis to differentiate COVID-19 from other viral pneumonia patients. With clinical symptoms, laboratory testing results, and contact or travel history, the artificial intelligence system can help doctors identify patients … Continue reading
Imaging of coronavirus disease 2019 part 24
The artificial intelegence – system has outstanding perfomance in the detection of subtle GGO, which is the most easily missed typical CT feature of COVID-19. Also, it can precisely segment the lesion region, calculate the lesion volume, volume rates of … Continue reading
Imaging of coronavirus disease 2019 part 23
Application of artificial intelligence (AI) in COVID-19 A large amount of CT images makes it difficult for radiologists to compare among serial studies. Thus, rapid detection, accurate location of lesions, and evaluation of lesion size, properties, and lesion dynamics are … Continue reading
Imaging of coronavirus disease 2019 part 22
Streptococcus pneumonia is characterized by the consolidation of lobes or lobules without GGO. Both mycoplasma and aspiration peumonia distribute along bronchovascular bundle, which is significantly different from COVID-19 pneumonia. In study comparing chest CT from 219 patients with COVID-19 pneumonia … Continue reading
Imaging of coronavirus disease 2019 part 21
Differential diagnosis with other pneumonia Although the imaging features of COVID-19 overlap with those of SARS and MERS, there are differences on imaging exams that set the COVID-19 pnemonia apart. It is essential to make a differential diagnosis for early … Continue reading