Title :
Models for biomedical image reconstruction based on integral approximation methods
Author :
Byrne, Charles ; Gordon, Dan ; Heilper, Daniel
Author_Institution :
Dept. of Math. Sci., Univ. of Mass., Lowell, MA, USA
Abstract :
The most common image representation method for biomedical image reconstruction uses pixels, and the image is assumed to be constant throughout the pixel. Other methods have also been used. In many reconstruction problems, the measured data is approximated by line integrals through the object. This fact suggests a new class of model representation methods based on classical Newton-Cotes methods of integral approximations. These methods use Lagrange polynomials of one variable, and they can be extended to higher dimensions by blending. In 2D, these methods lead to the pixel model, bilinear interpolation, and higher order models. The bilinear interpolation model has been implemented and shown to be superior to the pixel model.
Keywords :
image reconstruction; image representation; integral equations; interpolation; medical image processing; Lagrange polynomials; Newton-Cotes method; bilinear interpolation model; biomedical image reconstruction; blending; higher order model; image representation method; integral approximation method; model representation method; pixel model; Biological system modeling; Biomedical measurements; Function approximation; Image reconstruction; Least squares approximation; Mathematical model; Basis functions; biomedical image reconstruction; integral approximation;
Conference_Titel :
Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4577-1857-1
DOI :
10.1109/ISBI.2012.6235486