Digital subtraction radiography detects
tissue mass changes by subtracting two digital radiographs. This method has shown to be very useful in early diagnosis
of disease and follow-up examination. When subtracting two radiographs taken over time, the image features which are
coincident to both images can be removed and the small changes can be amplified to highlight their presence.
For many years, digital subtraction radiography in dentistry has been used to qualitatively assess changes in radiographic
density. Numerous authors have demonstrated the ability of this method to improve diagnostic performance for the detection
of approximal dental caries, periapical pathology and periodontal disease. The use of digital subtraction radiography
has also been shown to markedly increase the detection of destruction in the periodontal bone, as well as secondary
A large variety of odontological diseases result in destruction of mineralized tissues, which are relatively small in
the initial progression of the disease. A reliable detection and follow-up examination necessarily requires a precise
alignment of the two images for the tissue changes to be detectable. Different approaches have been proposed for correcting
such geometrical distortions. It goes from manual correction to different devices used to ensure a consistent geometric
projection with can be reliably reproduced over time.
In this research, an entirely automatic method is proposed for spatial radiographic alignment. The process starts by
selecting either of the two images as the reference while the other is considered the floating image. Afterward illumination
differences are eliminated by means of an equalization algorithm explained below. Then consecutive affine transformations
are performed on the floating image and the transformed image is compared to the reference using the correlation ratio
as the similarity measure. An adaptive GA is used in order to find the transformation that produces the best match.
The process is robust, reliable and reproducible on the test group of images.