Automatic identification of crossovers in cryo‐EM images of murine amyloid protein A fibrils with machine learning

Abstract

Detecting crossovers in cryo-electron microscopy images of protein fibrils is an important step towards determining the morphological composition of a sample. We propose a combination of classical, stochastic approaches, and machine learning techniques towards solving this problem in a novel, much easier way.