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Two algorithms for the three‐dimensional reconstruction of tomograms
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1988
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Three‑dimensional surface reconstructions allow visualization of complex anatomy from CT, MRI, or SPECT tomograms, yet existing methods rely on distance from an imaginary viewpoint and surface normals. This study proposes that using the normalized gradient of the original tomographic values yields a more accurate surface normal and higher‑quality 3‑D images. Two algorithms that generate 3‑D surface models with polygon and point primitives for CAD integration are presented. The algorithms produce detailed 3‑D images of bony and soft tissues, including the skull, spine, internal air cavities, and abdominal aorta.
Three‐dimensional (3‐D) surface reconstructions provide a method to view complex anatomy contained in a set of computed tomography (CT), magnetic resonance imaging (MRI), or single photon emission computed tomography tomograms. Existing methods of 3‐D display generate images based on the distance from an imaginary observation point to a patch on the surface and on the surface normal of the patch. We believe that the normalized gradient of the original values in the CT or MRI tomograms provides a better estimate for the surface normal and hence results in higher quality 3‐D images. Then two algorithms that generate 3‐D surface models are presented. The new methods use polygon and point primitives to interface with computer‐aided design equipment. Finally, several 3‐D images of both bony and soft tissue show the skull, spine, internal air cavities of the head and abdomen, and the abdominal aorta in detail.