An approach to automatically group age-related macular degeneration (AMD) patients having similar retinal health profiles by clustering Optical Coherence Tomography (OCT) images is described. Spatial health patterns within and across profiles are discovered by identifying segments of images that have similar levels of health in a given retina region. Segmentations of various sizes are considered and the segmentation where the segment similarity most closely matches the discovered health profiles is used to identify health patterns. Our experiments with OCT images of 10 AMD patients show that - i) health profiles generated by clustering closely correspond to those identified by a physician expert, ii) a rich set of spatial patterns can be discovered within and across profiles using regular image segmentation, and iii) new images can be successfully classified into existing profiles so that physicians can provide effective profile-based treatments.