Try out this interactive tutorial on convolutional neural network (CNN) noise reduction for CT imaging, available online here. Deep learning image processing methods have attracted interest in the CT community due to their ability to dramatically reduce image noise and artifacts while maintaining fine anatomic structures. The CT CIC has explored the potential of using deep learning techniques to improve diagnostic quality and reduce radiation dose. This tutorial was created by Nathan Huber and Andrew Missert in collaboration with Dr. Erickson as an educational tool for individuals interested in learning about how to implement CNN noise reduction. This work as presented at RSNA and recently published in Radiology AI. Article can be found here.