Bone and cartilage segmentation models were trained and validated with a segmented dataset of 40 and 176 3D DESS MRI volumes respectively. The trained models were used to run inference on 20,989 3D DESS MRI volumes from the Osteoarthritis Initiative dataset. Biomarkers such as femoral bone shape, cartilage thickness and cartilage T2 average values were extracted from the segmentations. Point clouds representing each biomarker were transformed into spherical coordinates and merged using different fusion strategies. The spherical maps were used to train an OA diagnosis model with a test specificity, sensitivity and AUC was 84.1%, 78.7%, and 89.7% respectively.