Machine Learning for Tomographic Imaging

Wednesday, October 16, 2019 - 3:00pm - 3:45pm
Keller 3-180
Ge Wang (Rensselaer Polytechnic Institute)
Computer vision and image analysis are major application examples of deep learning. While computer vision and image analysis deal with existing images and produce features of these images (images to features), tomographic imaging produces images of multi-dimensional structures from experimentally measured “encoded” data as various tomographic features (integrals, harmonics, and so on, of underlying images) (features to images). Recently, deep learning is being actively developed worldwide for tomographic imaging, forming a new area of imaging research. In this presentation, we focus on a perspective on deep reconstruction, promising results, and related interpretability analysis.