Abstract: Image indexing for biomedical content is a prohibitively expensive task if done manually. This leads to the demand for effective automated or computer assisted indexing methods. We are doing research on this problem for a set of digitized x-ray films from the second National Health and Nutrition Examination Survey (NHANES II). The 10,000 cervical spine and 7,000 lumbar spine images from this survey are retrievable through a resource we have developed, the Web-based Medical Information Retrieval System (WebMIRS). Using WebMIRS, the user may retrieve x-rays based on text data, such as demographics, health questionnaire responses, or physican's examination results. Two National Institutes of Health workshops have identified visual features of the images specifically related to osteoarthritis, but the images have never been indexed for these features, which include anterior osteophytes, disc space narrowing, and subluxation. We are investigating the methods by which the indexing and retrieval of the images using these particular features, may be achieved, in a validated manner acceptable to the biomedical community. In this paper we review our work to date, plus the work of collaborating researchers, and present some possible outcomes that appear to be realistic