Speaker
Description
Magnetic resonance imaging (MRI) is well known as a non-invasive diagnostic imaging technique available to clinical medicine. MRI provides high spatial resolution images with flexible soft tissue contrast as the signal encoding is more complicated than other imaging modalities.
Machine learning, especially deep learning, has become a popular research topic to solve nonlinear problems. It has played an important role in many areas, from self-driving car to chatGDP. The MRI research community has embraced the opportunity and exploited the powerful tool in image classification/feature detection, and signal processing/image reconstruction. However, diagnostic imaging presents different challenges compared to other digital image processing tasks such as computer vision. In this talk, I will present the capabilities and potential pitfalls of deep learning, focusing on the applications in MRI.
| Keyword-1 | Magnetic Resonance Imaging |
|---|---|
| Keyword-2 | Deep Learning |
