Scatter Removal in Dynamic X-Ray Tomography using Learned Robust Features

Abstract

A challenging problem in industrial radiography is accurate density reconstructions from X-ray projections corrupted by noise, scatter, etc. We propose a deep learning-based framework to extract robust features from radiographs and reconstruct the underlying densities.