15 April 1996 New interpolation algorithm for three-dimensional medical image reconstruction
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Many medical applications require the full perception of human organs or tissues for advanced interpretation and reliable decision. It is useful to generate a three-dimensional (3-D) view from its serial cross sections for surgical planning and diagnosis. The cross-sectional images are usually represented by contours after segmentation. Interpolation has to be carried out to fill the space between the successive contours. A new approach to 3-D image interpolation using the co-matching corresponding finding (CMCF) is proposed. The start and goal contours are mapped onto a unit square respectively and then divided into four regions with each side of the square in order to determine the four bounding points. Four segments are formed between the bounding points. Hence, the matching process becomes the matching of a segment to another (segment of another contour) and it is repeated four times. An objective mapping is applied to the correspondence points of each segment and additional points which follow a precise decision rule may be inserted for determining the best correspondence pair.
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Sau-hoi Wong, Sau-hoi Wong, Kwok-Leung Chan, Kwok-Leung Chan, } "New interpolation algorithm for three-dimensional medical image reconstruction", Proc. SPIE 2707, Medical Imaging 1996: Image Display, (15 April 1996); doi: 10.1117/12.238482; https://doi.org/10.1117/12.238482

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