You’ll learn how to apply deep learning to radiology and medical imaging in this class. The workshop covers:
Ideally, students in this course has a basic familiarity with deep neural networks, either through the DLI Fundamentals of Computer Vision course or another online training program. Basic coding experience in python or a similar language is also useful.
Basic familiarity with deep neural networks, Basic coding experience in python or a similar language
Learn to apply CNNs to MRI scans plus:
Introduction
Introductions, account creation, and troubleshooting
Image Segmentation
Learn techniques for placing each pixel of an image into a specific class
Image Analysis
Leverage Convolutional neural networks (CNNs) for medical image analysis to infer patient status from non-visible images. Train a CNN to infer the volume of the left ventricle of the human heart from time-series MRI data
Image Classification with TensorFlow
Learn about the work being performed at the Mayo Clinic, using deep learning techniques to detect Radiomics from MRI imaging that has led to more effective treatments and better health outcomes for patients with brain tumors
Closing remarks
A quick overview of the next -steps you could leverage to build and deploy your own applications and any Q&A