The effect of random coincidences estimation methods on the quantitative accuracy of iterative and analytic reconstruction methods to determine myocardial blood flow (MBF) in PET studies using H<sub>2</sub> <sup>15</sup>O has been investigated. Dynamic scans were acquired on the EXACT3D PET scanner on pigs after H<sub>2</sub> <sup>15</sup>O injection (resting and dipyridamoleinduced stress). Radioactive microspheres (MS) were used to provide a "gold standard" of MBF values. The online subtraction (OS) and maximum likelihood (ML) methods for estimating randoms were combined with (i) 3D-RP, (ii) FORE + attenuation-weighted OSEM, (iii) FORE-FBP and (iv) 3D-OSEM. Factor images were generated and resliced to short axis images; 16 ROIs were defined in the left myocardium and 2 ROIs in the left and right cavities. ROIs were projected onto the dynamic images to extract time-activity-curves, which were then fitted to a single compartment model to estimate absolute MBF. Microsphere measurements were obtained in a similar way and 64 pairs of measurements were made. The ML method improved the SNR of 3D-RP, FORE-FBP, FORE-OSEM, and 3D-OSEM by 8%, 8%, 7% and 3% respectively. Compared to the OS method, the ML method improved the accuracy of coronary flow reserve values of 3DOSEM, 3D-RP, FORE-OSEM and FORE-FBP by 9%, 7%, 1% and 3% respectively. Regression analysis provided better correlation with 3D-OSEM and FORE-OSEM when combined with the ML method. We conclude that the ML method for estimating randoms combined with 3D-OSEM and FORE-OSEM delivers the best performance for absolute quantification of MBF using H<sub>2</sub> <sup>15</sup>O when compared with microsphere measurements.