Evaluation of Scalar Value Estimation Techniques for 3D Medical Imaging
AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING
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Scalar value estimation in 3D medical imaging increases data resolution for enhanced renditions and corrects inaccurate surface formations. Accurate estimations are vital because clinical assessment is often aided by examination of 3D medical images. This thesis explores different estimation techniques and introduces the geostatistical estimation technique called kriging to the field of 3D imaging. Kriging theory claims to be the optimal estimator-- better than the standard deterministic methods commonly used. The techniques investigated are linear interpolation, trilinear interpolation, tricubic interpolation, and kriging. This research investigates scalar value estimation in the volume pre-processing operation of slice interpolation and in a surface extraction method called cell subdivision. Tricubic interpolation is shown to be most useful in artificially created volumes of smooth functions. It is also shown to produce poor results in medical volumes and in slice interpolation. More importantly, this research demonstrates that kriging subsumes the deterministic methods investigated and can estimate much better than tricubic interpolation.
- Computer Programming and Software