High-sensitivity miniature optically pumped magnetometers (OPMs) enable noninvasive magnetocardiography (MCG) with flexible sensor configurations. Accurate magnetic source imaging (MSI) critically depends on precise registration between MCG measurements and anatomical computed tomography (CT) data, while registration errors can substantially degrade source localization accuracy. In this study, we systematically analyze the data acquisition and coordinate transformation processes to identify major sources of registration error in OPM-MCG systems. We show that existing approaches often overlook sensor pose deviations introduced by substituting the manufactured sensor array with an ideal design model during registration. To address this limitation, we propose an optical image–based sensor array calibration method using the local tangent plane distance (LTPD) measure and a sensor face filtering (SFF) algorithm. The proposed method directly extracts sensor positions and orientations without relying on predefined array parameters, thereby correcting errors caused by sensor assembly inaccuracies and array deformation. Experimental results demonstrate a mean position error of 0.53 mm and an orientation error of 0.84° for the sensitive axis. In addition, we investigate the effects of data volume and registration algorithm selection on transformation accuracy, revealing their critical roles in achieving high-precision registration. The optimized registration pipeline improves both accuracy and computational efficiency, facilitating reliable MSI for both rigid and wearable OPM-MCG systems.