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19 November 2003 Volume reconstruction of medical images by moment-based transfer function
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Abstract
Three-dimensional medical reconstruction has been a powerful technique in medical diagnosis, especially by using volume visualization of medical datasets such as those obtained from computed tomography (CT), magnetic resonance imaging (MRI) in recent years. A new medical volume reconstruction algorithm is presented in this paper. By examining the relations among three eigenvalues of local block based moment (LBBM) inertia matrix, the method defines transfer function in the domain of these eigenvalues. The eigenvalues and eigenvectors of the LBBM inertia matrix form a local coordinate system, which measures the local features such as flat, round, and elongated shapes of the object. The optimal window size of local voxel block is determined by experiments, and then two popular volume visualization algorithms are implemented to test the proposed transfer function design method. The proposed method can efficiently depict trivial features in medical datasets, especially useful in the rendering of structures with obvious shapes, such as round, flat, and elongated shapes. The new algorithm can not only result informative rendering results to the doctors, but also can efficiently reduce the time previously spent in trial-and-error process.
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Jiawan Zhang, Jizhou Sun, and Zhigang Sun "Volume reconstruction of medical images by moment-based transfer function", Proc. SPIE 5203, Applications of Digital Image Processing XXVI, (19 November 2003); https://doi.org/10.1117/12.505372
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