Inflammatory joint diseases (e.g. rheumatoid arthritis) affect joints in human body leading first to painful joints and after a long time without treatment to permanent joint damage. Patients become physically deprived and find it more difficult to perform daily activities. In some cases, a complete inability to perform activities may occur. Therefore quality of their lives is significantly reduced. To prevent long-term consequences and improve their quality of life as much as possible, it is necessary to start with appropriate treatment as early as possible.
Diagnosis in Slovenia is most often performed by clinical and ultrasound examination. Because this type of examination is slow and requires an experienced physician, there is a need for newer, faster, and more accurate diagnostic techniques.
Within this thesis, we therefore explored the possibility of using RGB (red - green - blue) hand images to detect arthritis of the small joints of hands.
The captured RGB images of patients' hands were first corrected with a curvature correction algorithm to remove illumination artifacts from RGB images, such as shadows on the areas with larger curvatures. Next, the images are converted to the CIEXYZ color space, and finally XYZ images are associated with physiological properties such as blood volume fraction and blood oxygen saturation.
Analysing a collection of images of 29 patients with rheumatoid and psoriatic arthritis, we estimated that this approach is not yet useful for the diagnosis of inflammation of the small joints of hands. However, we suggest a way to improve the approach so that the dissease detection could be made.