Figure 8 from Optical tomography using the time-independent equation of radiative transfer-Part 1: Forward model | Semantic Scholar (2024)

Numerical simulations with synthetic data show that the cross-talk between the two optical parameters is significantly reduced in reconstructions based on frequency-domain data as compared to those based on steady-state data.

A deep generative model is proposed to reconstruct the fluorescence distribution map from CW fluorescence measurements, which is the first time that such a model is applied for fluorescence DOT image reconstruction.

The application of model-based image reconstruction is reviewed, together with a numerical modelling approach to light propagation in tissue as well as generalized image reconstruction using boundary data, whereby the use of spectral and dual-modality systems can improve contrast and spatial resolution.

A new way of predicting the short-pulsed NIR light propagation using a time-dependent two-dimensional-global radiative transfer equation in an absorbing and strongly anisotropic scattering medium is presented and a cell-vertex finite-volume method is proposed for the discretization of the spatial domain.

An algorithm using data acquired with a time-resolved system with the goal of reconstructing sources of fluorescence emanating from the deep interior of highly scattering biological tissues is presented and a new least-squares solver with bound constraints adapted for optical problems where a physical non-negative constraint can be imposed is introduced.

A FDM was developed for solving two-dimensional RTE in a 2cm×2cm square hom*ogeneous tissue with two groups of the optical properties and different schemes of the spatial and solid angle discretization and it is shown that when the step size ofThe spatial mesh becomes small, more discretized angle number is needed.

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An iterative image reconstruction scheme for optical tomography that is based on the equation of radiative transfer that accurately describes the photon propagation in turbid media without any limiting assumptions regarding the optical properties is reported on.

In this contribution, the image reconstruction algorithm is formulated as an optimization problem in which an interior map of tissue optical properties of absorption and fluorescence lifetime is reconstructed from synthetically generated exterior measurements of frequency-domain photon migration (FDPM).

This paper considers models based on radiative transfer theory and its derivatives, which are either stochastic in nature (random walk, Monte Carlo, and Markov processes) or deterministic (partial differential equation models and their solutions).

The group has developed approaches to image reconstruction which have the potential advantages of directly yielding an image without the need for numerical reconstruction and has emphasized the first two of the four methods.

Numerical studies suggest that intraventricular hemorrhages can be detected using the GIIR technique, even in the presence of a heterogeneous background.

The tomographic method presented here can provide a basis for rapid, real-time medical monitoring by the use of optical projections and can be combined with the optical tissue diagnosis methods based on spectroscopic molecular signatures to result in a versatile optical diagnosis and imaging technology.

The results show that although it is possible to obtain qualitative visual information on the location and size of a heterogeneity, it may not be possible to quantitatively resolve contrast levels or optical properties using reconstructions from DC data only.

This work presents the underlying concepts in their approach to overcome ill-posedness in optical tomography and shows numerical results that demonstrate how prior knowledge, represented as penalty terms, can improve the reconstruction results.

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