We illustrate the application of intelligent medical image analysis techniques in order to reduce the computational cost of statistical voxel-wise analysis for detecting discriminative regions of morphological variability among different populations. We demonstrate that novel statistical image processing techniques that operate selectively on groups of pixels are suitable for morphological analysis of anatomical structures visualized by modern medical imaging modalities. We also show that the proposed methodology effectively decreases the number of statistical tests performed, alleviating the effect of the multiple comparison problem. We show that our approach detects regions of statistically significant morphological variability. Our results validate previous findings, while being robust across a wide range of experimental settings.