In Cardiac MRI, Late gadolinium enhancement (LGE) imaging is generally performed for the assessment of myocardial viability. As LGE is based on inversion recovery techniques, the correct myocardial nulling is necessary for image contrast optimization. In current clinical practice, it is done by visual evaluation. As it required user expertise and interaction, an automated inversion time selection is proposed. The Deep-Learnig-based system to detect the null point of inversion time was successfully demonstrated in all datasets comparing with two expert annotations.