Affordable COVID-19 Diagnoses for Hospitals: How Open Source Software Helps

Basically, what a hospital needs to accomplish is to eliminate spots on the CT scan image that are "less important" -- meaning, in this application, spots that don't reflect the actual image of the lungs. That can be done through a common algorithm called singular value decomposition (SVD). To apply the SVD, a little preprocessing is necessary. A CT scan image is normally represented in three dimensions. One dimension is a series of "slices," each slice being a two-dimensional image. The SVD algorithm requires a two-dimensional matrix, but it's easy to reduce three dimensions to two: just string out the rows of each two-dimensional matrix, as you might unfold a fold-up walking stick or measuring stick. The SVD algorithm produces a new set of matrices with powerful properties.