Models for biomedical image reconstruction based on integral approximation methods

Charles Byrne, Dan Gordon, Daniel Heilper

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publication2012 9th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2012 - Proceedings
Pages70-73
Number of pages4
DOIs
StatePublished - 2012
Event2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 - Barcelona, Spain
Duration: 2 May 20125 May 2012

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012
Country/TerritorySpain
CityBarcelona
Period2/05/125/05/12

Keywords

  • Basis functions
  • biomedical image reconstruction
  • integral approximation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Fingerprint

Dive into the research topics of 'Models for biomedical image reconstruction based on integral approximation methods'. Together they form a unique fingerprint.

Cite this