Measurement Reduction Methods for Processing Tomographic Images

The importance of development of new methods for reconstruction of an object image given its sinogram and some additional information about the object stems from the possibility of artifact presence in the reconstructed image, or its insufficient sharpness when the used additional information does not hold. The problem of recovering artifact-free images of the studied object from tomography data is considered in the framework of the theory of computer-aided measuring systems. Methods for solving it are developed. They are based on narrowing the class of possible images using less artifact-inducing information. An example of such information is the natural condition of non-negativeness of the estimated brightnesses. The main problem that arises is the large dimensionality of the images, which prevents the use of direct algorithms. One proposed method is based on local approach, namely correction of the result of unfiltered backprojection by applying a locally (in the space of the output image) optimal linear transformation. Another method processes a sinogram directly, without using backprojection, using iterative implementation of the measurement reduction technique. Examples of use of the proposed methods for processing teeth sinograms are given.

Automated summary

The development of new methods to reconstruct object images given their sinogram and additional information is important due to the possibility of artifacts or lack of sharpness in the reconstructed image. This problem is addressed in the field of computer-aided measuring systems, and methods have been developed to solve it by narrowing down the range of possible images using less artifact-inducing information. These methods include local correction of unfiltered backprojection and direct processing of the sinogram using iterative implementation of measurement reduction technique. Examples of these methods applied to teeth sinograms are provided.