Rheumatoid arthritis (RA) is a chronic disease that affects and potentially destroys the joints of the appendicular skeleton. The precise and reproducible quantification of the progression of joint space narrowing and the erosive bone destructions caused by RA is crucial during treatment and in imaging biomarkers in clinical trials. Current manual scoring methods exhibit high interreader variability, even after intensive training, and thus, impede the efficient monitoring of the disease. We propose a fully automatic quantitative assessment of the radiographic changes that result from RA, to increase the accuracy, reproducibility, and speed of image interpretation. Initial joint location estimates are obtained by local linear mappings based on texture features. Bone contours are delineated by active shape models comprised of statistical models of bone shape and local texture. These models are refined by snakes which increase the accuracy and allow for a fitting of pathological deviations from the training population. The method then measures joint space widths and detects erosions on the bone contour. Joint space widths are measured with a coefficient of variation of 2%-7% for repeated measurements and erosion detection exhibits an area under the receiver operating characteristic (ROC) curve of 0.89. Model landmarks serve as a reference system along the contour. These landmarks enable the definition of joint regions and more specific follow-up monitoring. The automatic quantification allows for a remote analysis, relevant for multicenter clinical trials, and reduces the workload of clinical experts since parts of the process can be managed by nonexpert personnel.