|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
SURFACE INTERPOLATION FROM SPARSE CROSS-SECTIONS USING REGION CORRESPONDENCE
G.M.Treece, R.W.Prager, A.H.Gee and L.Berman.
The ability to estimate a surface from a set of cross-sections allows calculation of the enclosed volume and the display of the surface in three-dimensions (3-D). This process has increasingly been used to derive useful information from medical data. However, extracting the cross-sections (segmenting) can be very difficult, and automatic segmentation methods are not sufficiently robust to deal with all situations. Hence, it is an advantage if the surface reconstruction algorithm can work effectively on a small number of cross-sections. In addition, cross-sections of medical data are often quite complex. In this paper, an algorithm is presented which can interpolate a surface through sparse, complex cross-sections. This is an extension of maximal disc guided interpolation, which is itself based on shape based interpolation. The performance of this algorithm is demonstrated on various types of medical data (X-ray Computed Tomography, Magnetic Resonance Imaging and three-dimensional ultrasound). Although the correspondence problem in general remains unsolved, it is demonstrated that correct surfaces can be estimated from a limited amount of real data, through the use of region rather than object correspondence.
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