||Electrocardiographic Imaging (ECGI) is a computational approach that seeks to reconstruct cardiac electrical activity with high precision from body surface ECGs by solving a numerical inverse problem. Though there have been great advancements in ECGI, there is still a need for progress in specific applications, including discernment of ectopic foci and reconstruction of other arrhythmias. In order to improve and validate the localization of ectopic regions using ECGI, it is necessary to record high resolution ECGs known as " body surface potential maps " during stimulation of the heart from known ectopic foci. Such measurements typically occur in the catheterization lab during invasive procedures such as device placement or during diagnostic evaluation of cardiac electrical stability using catheter based stimulation electrodes. However, there are spatial constraints on electrode placement on the body, such as defibrillator patches (for patient safety) and sterile fields. (for device implantation). To overcome the resulting limits in body surface electrode placement and coverage, one can use estimation algorithms to utilize spatial redundancy and draw equivalent data from reduced numbers of strategically place electrodes. In this study, we applied a body surface estimation and limited lead selection algorithm to body surface mapping data and determined a patient specific lead placement strategy to acquire body surface maps in ECGI verification studies.