Fusion and display of 3D SPECT and MR images registered by a surface fitting method

Since 3D medical images such as SPECT and MRI are taken under different patients positioning and imaging parameters, interpretation of them, as reconstructed originally, does not provide an easy and accurate understanding of similarities and differences between them. The problem becomes more crucial where a clinician would like to map accurately region of interest from one study to the other, by which some surgical or therapeutical planning may be based. The research presented here is an investigation into the problems of the registration and display of brain images obtained by different imaging modalities. Following the introduction of an efficient method some clinical useful application of the registration and superimposition were also defined. The various widely used registration algorithms were first studied and their advantages and disadvantages of each method were evaluated. In this approach, an edge-based algorithm (Called surface fitting), which are based on a least-square-distance matching, were suggested for registering of brain images. This algorithm minimizes the sum of square-distances between the two surfaces obtained from two modalities. The minimization is performed to find a set of six geometrical transformation parameters (3 shifts and 3 rotations) which indicate how one surface should be transformed in order to match with the other surface.