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      Computer-aided interpretation of SPECT images of the brain using an MRI-derived 3D neuro-anatomical atlas

      , , , , , ,
      Medical Informatics
      Informa UK Limited

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          Abstract

          Nuclear medicine images have comparatively poor spatial resolution, making it difficult to relate the functional information which they contain to precise anatomical structures. A 3D neuro-anatomical atlas has been generated from the MRI data set of a normal, healthy volunteer to assist in the interpretation of nuclear medicine scans of the brain. Region growing and edge-detection techniques were used to semi-automatically segment the data set into the major tissue types within the brain. The atlas was then labelled interactively by marking points on each 2D slice. Anatomical structures useful in the interpretation of SPECT images were labelled. Additional, more detailed information corresponding to these structures is provided via an interactive index which allows access to images, diagrams and explanations. Registration of patient SPECT studies with the atlas is accomplished by using the position of the skull vertex and four external fiducial markers attached to the skin surface. The 3D coordinates determined from these points are used to calculate the transformation required to rotate, scale and translate the SPECT data, in 3D, to match the atlas. Corresponding 2D slices from the two 3D data sets are then displayed side-by-side on a computer screen. A cursor linking the two images allows the delineation of regions of interest (ROIs) in the SPECT scan based on anatomical structures identified from the atlas. Conversely regions of abnormal isotope distribution in the SPECT image can be localized by reference to corresponding structures in the atlas.

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          Most cited references15

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          Two point sets {pi} and {p'i}; i = 1, 2,..., N are related by p'i = Rpi + T + Ni, where R is a rotation matrix, T a translation vector, and Ni a noise vector. Given {pi} and {p'i}, we present an algorithm for finding the least-squares solution of R and T, which is based on the singular value decomposition (SVD) of a 3 × 3 matrix. This new algorithm is compared to two earlier algorithms with respect to computer time requirements.
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                Author and article information

                Journal
                Medical Informatics
                Medical Informatics
                Informa UK Limited
                0307-7640
                July 12 2009
                July 12 2009
                January 1991
                : 16
                : 2
                : 151-166
                Article
                10.3109/14639239109012124
                1921560
                daa36ef9-79cc-44c7-bee7-2feba3f77250
                © 1991
                History

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