Accession Number : ADA297364

Title :   Biomedical Data Interpolation for 3-D Visualization.

Descriptive Note : Master's thesis,

Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH

Personal Author(s) : Chen, Ming-Chung

PDF Url : ADA297364

Report Date : JUN 1995

Pagination or Media Count : 114

Abstract : Medical imaging devices that produce three-dimensional data usually produce the data in the form of image slices. In such images, the resolution in z direction is lower than in x and y directions. Before extracting and displaying objects in such images, an interpolated 3-D gray-scale volume image can be generated via image interpolation techniques to fill in the missing information. The subject of this thesis is the applying three different interpolation techniques to generate intermediate slices and comparing their qualities. The three interpolation techniques are linear interpolation, cubic spline interpolation, and Fourier in terpolation. We also apply the CT image matching method, developed by Ardeshir Coshtasby, David A. Turner, and Laurens V. Ackerman, which can determine the correspondence between points in two images. Finally, we use the human visual perception model to measure the qualities of interpolation images. Linear interpolation is shown to be the best of the three interpolation techniques used in this thesis. This research also shows that without the image segmentation or the image matching process poor intermediate images will be generated.

Descriptors :   *IMAGES, *VISUAL PERCEPTION, *MEDICAL SERVICES, MODELS, HUMANS, THESES, X RAYS, THREE DIMENSIONAL, LINEARITY, INTERPOLATION, MATCHING, RADIOGRAPHY, BIOMEDICINE, CUBIC SPLINE TECHNIQUE.

Subject Categories : Anatomy and Physiology
      Medicine and Medical Research
      Optics

Distribution Statement : APPROVED FOR PUBLIC RELEASE