MRI is noninvasive and generates clear images, giving it great potential as a diagnostic instrument. However, current methods of image analysis are too time-consuming for dynamic systems such as the cardiovascular system. Since dynamic imagery generate a huge number of images, a computer aided machine vision diagnostic tool is essential for implementing MRI-based measurement. In this paper, a wavelet-based image technique is applied to enhance left ventricular endocardial and epicardial profiles as the preprocessor for a dynamic programming-based automatic border detection algorithm. Statistical tests are conducted to verify the performance of the enhancement technique by comparing borders manually drawn with 1. borders generated from the enhanced images, and 2. borders generated for the original images.