Heart failure is the clinical syndrome accompanying the inability of the heart to maintain a cardiac output required to meet the metabolic requirements and accommodate venous return, and is one of the leading causes of mortality in United States. Accurate imaging of the heart and its failure is important for successful patient management and treatment. Multiple cardiac imaging modalities provide complementary information about the heart – LV function and wall motion, anatomy, myocardial viability and ischemia. In many instances, it is necessary for a patient to undergo multiple imaging sessions to obtain diagnostic clinical information with confidence. It would be beneficial to the individual and the health care system if a single imaging modality could yield reliable clinical information about the heart, leading to a reduced cost, anxiety and an increased diagnostic confidence. This thesis proposes methods that would make cardiac MRI perform an improved assessment of LV function, wall motion, and viability, such that cardiac MRI is taken one step closer to being a single stop solution for imaging of heart. Conventional cardiac MR imaging is performed at a temporal resolution of around 40 ms per cardiac phase. While the global left ventricular (LV) function can be reliably established at this temporal resolution, functional metrics characterizing transient function like peak filling and ejection rates are not accurately assessed. A high temporal resolution is necessary to characterize such transient LV function and wall motion mechanics. This thesis proposes methods to acquire cine-images of the heart at a higher temporal resolution (~ 6 ms) and algorithms to acquire the LV volume across all cardiac phases that would yield functional metrics characterizing LV function and wall motion mechanics. The validation of these algorithms was performed on human subjects. Cardiac MR imaging is the current gold standard of myocardial viability imaging, in which scarred regions of the heart following myocardial infarction are visualized. However viability imaging faces image quality challenges in patients with severe arrhythmias and in cases where a higher spatial resolution, and hence a longer acquisition time, is desired. This thesis also proposes an arrhythmia insensitive inversion recovery (AIIR) algorithm that would significantly reduce artifacts that degrade image quality, thereby extending viability imaging to higher spatial resolution and in patients with severe arrhythmia. Simulations, experimental validation on phantoms and clinical verification on patients are performed. Results from high temporal resolution imaging reveal that obtaining cine cardiac MR images at a temporal resolution of 6 ms per cardiac phase is feasible. Appropriate validated algorithms yield LV time-volume curve from which LV functional metrics are reliably extracted. A dependence on temporal resolution is revealed, and a temporal resolution cut-off of 12 ms is proposed to reliably capture the temporal dynamics of the LV. Also, results from cardiac viability imaging show that the AIIR algorithm performs significantly better than conventional imaging methods in both phantoms and human subjects, as shown by the blinded expert scores, leading to a better image quality. In conclusion, this thesis proposes and implements methods that help cardiac MRI yield 1) a better function and wall motion assessment of the heart through high temporal resolution imaging and 2) a better assessment of myocardial viability through the AIIR algorithm.