Convolutional neural network pipeline has 100% accuracy distinguishing between COVID and pneumonia
A fully automatic pipeline of convolutional neural networks and capsule networks was able to accurately differentiate between COVID-19 and community-acquired pneumonia (CAP) on chest CT images, according to new research.
Chest CTs have been crucial in achieving a timely diagnosis for patients who present with symptoms consistent with COVID. However, COVID-19 and CAP have similar appearances on such scans. It can be difficult for a radiologist to accurately differentiate between the two, but doing so is pertinent to a patient’s treatment plan.
The researchers proposed using a fully automatic pipeline of convolutional neural networks (CNNs) and capsule networks to assist radiologists in discerning between COVID and CAP.