Synopsis

Cardiovascular Magnetic Resonance (CMR) is a safe technique, which can provide non-invasive gold-standard assessment of cardiac structure and function in patients with cardiovascular disease. While standard CMR imaging is relatively robust, some CMR techniques are inherently less reliable and image quality can be reduced. Besides, for high-resolution or 3D imaging, the acquisition duration is long and image quality may be further compromised. Recently, deep learning based methods have gained performance dividends in medical image analysis. In this talk, I will introduce the basic ideas of deep learning and its development and applications in CMR reconstruction and super-resolution towards future perspectives.