Intelligent Scanning Using Deep Learning for MRI – TensorFlow – Medium

Posted by Jason A. Polzin, PhD GM Applications and Workflow, GE Healthcare Global Magnetic Resonance Imaging Here we describe our experience using TensorFlow to train a neural network to identify specific anatomy during a brain magnetic resonance imaging (MRI) exam to help improve speed and consistency. MRI (Figure 1.) is a 3D imaging technique that allows clinicians to visualize structures in the body non-invasively and without ionizing radiation. MRI is a widely used and powerful imaging modality due to its superior contrast between "soft" tissues, e.g. One of the key strengths of MRI is being able to image specific locations in the body at an orientation best suited for the purpose of the exam. This means that the operator must plan these scans carefully to yield the best possible images uniquely oriented for each patient to visualize the specific structures that may be of interest.