Convolution is a mathematical concept that implies the product of two functions. In practical terms for radiology, convolution implies the application of a mathematical operation to a signal such that a different signal is produced. Convolutions are applied in image processing for CTs and MRIs.
Convolutions are the foundation of convolutional neural networks. In the computer vision setting, a small matrix will act as one 'function', and a matrix of image pixel values will act as the second 'function'. By multiplying the small matrix with a portion of the pixel matrix that is the same size as the former, and then continuing that process across the entire pixel matrix, we perform convolution.
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