Efficient processing of μCT images using deep learning tools for generating digital material twins of woven fabrics

The greatest challenge in creating digital material twins from μCT images is the lack of a robust and versatile tool for segmenting the μCT images and post-processing the segmented volumes into a FE mesh. Here, we have used deep convolutional neural networks (DCNN) for segmenting μCT images of a multi-layer plain-woven fabric. First, a set of raw 2D image slices extracted from the gray-scale volume of a single-layer fabric was used to train a...