Explore cutting-edge deep learning techniques for CT reconstruction in this insightful conference talk presented by Ge Wang and his research group from Rensselaer Polytechnic Institute. Delve into the applications of diffusion models and large-scale neural networks in computed tomography, gaining valuable insights into advanced image reconstruction methods. Learn how these innovative approaches are revolutionizing medical imaging and enhancing diagnostic capabilities in the field of radiology.
Overview
Syllabus
CT – Deep Learning with Diffusion & Large Models
Taught by
Yale Radiology and Biomedical Imaging
Tags
Related Courses
-
Visualizing the Living Body: Diagnostic Imaging
3.0 -
Deep Learning for Healthcare
-
Deep Learning Guided Reconstruction and Processing for PET, SPECT, and CT
-
Deep Learning for CT Reconstruction – Image Denoising and Beyond
-
Deep Learning with PyTorch for Medical Image Analysis
-
Integrating Image Quality Models into Deep CT Denoising
