Analytic surface reconstruction by local threshold estimation in the case of simple intensity contrasts

Peter J. Yim; Ronald M. Summers

doi:10.1117/12.349599

20 May 1999 Analytic surface reconstruction by local threshold estimation in the case of simple intensity contrasts

Peter J. Yim, Ronald M. Summers

Proceedings Volume 3660, Medical Imaging 1999: Physiology and Function from Multidimensional Images; (1999) https://doi.org/10.1117/12.349599
Event: Medical Imaging '99, 1999, San Diego, CA, United States

Abstract

Surface reconstruction for 3D visualization requires both a segmentation of the image and at the least, a conversion of the data from an image format to a shape format. While the discrete pixel locations of the segmentation may be satisfactory for quantitative purposes, it is usually important for visual quality to remove such voxelation in the shape data prior to rendering. Removal of such voxelation, depending on the specific segmentation technique, may be problematic, involving excessive interpolation prior to segmentation or the application of pure surface smoothing in which important image information may be disregarded. An algorithm is presented here to address these problems. In this algorithm, a smoothly varying threshold level is determined such that that level falls within the interpolated intensity ranges of all the segmentation-boundary voxels. This threshold information is extrapolated to voxels adjacent to the boundary and then used to correct or normalize the original image in the vicinity of the boundary. Provided that the directionality of the contrast between the interior and exterior of the boundary is sufficiently consistent throughout the boundary, an isosurface of this normalized image is guaranteed to exist which falls within the voxels of the segmentation boundary.

Citation Download Citation

Peter J. Yim and Ronald M. Summers "Analytic surface reconstruction by local threshold estimation in the case of simple intensity contrasts", Proc. SPIE 3660, Medical Imaging 1999: Physiology and Function from Multidimensional Images, (20 May 1999); https://doi.org/10.1117/12.349599

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