Calculating cardiac strains through speckle tracking echocardiography (STE) has shown promise as prognostic markers linked to functional indices and disease outcomes. However, the presence of acoustic shadowing often challenges the accuracy of STE in small animals such as rodents. The shadowing arises due to the complex anatomy of rodents, with operator dexterity playing a significant role in image quality. The effects of the semi-transparent shadows are further exacerbated in right ventricular (RV) imaging due to the thinness and rapid motion of the RV free wall (RVFW). The movement of the RVFW across the shadows distorts speckle tracking and produces unnatural and non-physical strains. The objective of this study was to minimize the effects of shadowing on STE by distinguishing “out-of-shadow” motion and identifying speckles in and out of shadow. Parasternal 2D echocardiography was performed, and short-axis B-mode (SA) images of the RVFW were acquired for a rodent model of pulmonary hypertension (n = 1). Following image acquisition, a denoising algorithm using edge-enhancing anisotropic diffusion (EED) was implemented, and the ensuing effects on strain analysis were visualized using a custom STE pipeline. Speckles in the shadowed regions were identified through a correlation between the filtered image and the original acquisition. Thus, pixel movement across the boundary was identified by enhancing the distinction between the shadows and the cardiac wall, and non-physical strains were suppressed. The strains obtained through STE showed expected patterns with enhanced circumferential contractions in the central region of the RVFW in contrast to smaller and nearly uniform strains derived from the unprocessed images.