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Optical imaging in medicine: II. Modelling and reconstruction
1Department of Computer Science, University College London, UK.
Physics in Medicine and Biology
|May 1, 1997
Summary
Developing diagnostic optical imaging relies on solving the inverse problem. This involves modeling photon transport to reconstruct internal tissue properties from light measurements.
Area of Science:
- Biomedical Optics
- Medical Imaging
- Computational Physics
Background:
- The need for non-invasive diagnostic optical imaging drives research into image reconstruction.
- Current methods often involve solving the inverse problem, assuming a unique internal scattering and absorption distribution can be determined from surface light measurements.
Purpose of the Study:
- To examine and review models developed for optical tomography image reconstruction.
- To discuss current approaches to solving the inverse problem in optical imaging.
Main Methods:
- Review of models based on radiative transfer theory, including stochastic (random walk, Monte Carlo, Markov processes) and deterministic (partial differential equations) approaches.
- Discussion of image reconstruction algorithms: direct backprojection, perturbation methods, nonlinear optimization, and Jacobian calculation.
Main Results:
- Identified various models for photon transport essential for optical tomography.
- Outlined diverse reconstruction algorithms applicable to optical imaging inverse problems.
Conclusions:
- Optical tomography requires robust models of photon transport and effective image reconstruction algorithms.
- Further research is needed to fully understand and realize the potential of optical tomography as a diagnostic tool.