Biomedical subjects

Franck Jaillon

Publications and source records attributed to Franck Jaillon.

4 recordsLinked to original sources

PubMed2006

Small-animal MRI: signal-to-noise ratio comparison at 7 and 1.5 T with multiple-animal acquisition strategies.

OBJECTIVE: The purpose of this study was to compare the signal-to-noise ratio (SNR) of phantom and rat brain images performed at 1.5 T on a clinical MR system and at 7 T on a small-animal experimental system. Comparison was carried out by taking into account SNR values based on a single sample acquisition at 1.5 and 7 T as well as on simultaneous imaging of multiple samples at 1.5 T. METHODS: SNR was experimentally assessed on a phantom and rat brains at 1.5 and 7 T using 25 mm surface coils and compared to theoretical SNR gain estimations. The feasibility of multiple-animal imaging, using the hardware capabilities available on the 1.5 T system, was demonstrated. Finally, rat brain images obtained on a single animal at 7 T and on multiple animals acquired simultaneously at 1.5 T were compared. RESULTS: Experimentally determined SNR at 7 T was far below theoretical estimations. Taking into account chemical shift, susceptibility artifacts and modifications of T1 and T2 relaxation times at higher field, a 7-T system holds limited advantage over a 1.5-T system. Instead, a multiple-animal acquisition methodology was demonstrated on a clinical 1.5-T scanner. This acquisition method significantly increases imaging efficiency and competes with single animal acquisitions at higher field. CONCLUSION: Multiple-animal imaging using a standard clinical scanner has a great potential as a high-throughput acquisition method for small animals.

Animals↗

PubMed2004

Geometric depolarization in patterns formed by backscattered light.

We formulate a framework to extend the idea of Berry's topological phase to multiple light scattering, and in particular to backscattering of linearly polarized light. We show that the randomization of the geometric Berry's phases in the medium leads to a loss of the polarization degree of the light, i.e., to a depolarization. We use Monte Carlo simulations in which Berry's phase is calculated for each photon path. Then we average over the distribution of the geometric phases to calculate the form of the patterns, which we compare with experimental patterns formed by backscattered light between crossed or parallel polarizers.

Computer Simulation↗

PubMed2003

Description and time reduction of a Monte Carlo code to simulate propagation of polarized light through scattering media.

Propagation of polarized light through a scattering medium has been studied with a Monte Carlo code to obtain polarized backscattered images. Studies of these backscattered patterns obtained with polarized illumination can be used as a technique to characterize the medium anisotropy factor g. First we present the different steps of the Monte Carlo simulation that describe polarized light propagation in a turbid medium. Monte Carlo is a good tool to simulate the backscattered polarized light but is time-consuming. Therefore, we consider two ways to decrease the computation time. The first way deals with angle sampling of the light direction. The second takes advantage of backscattered image symmetry to divide the simulation time by a factor of 4. By combining these two techniques we significantly decrease the code computation time.

Journal Article↗

PubMedDate not supplied

Scattering coefficient determination in turbid media with backscattered polarized light.

A simple empirical method is presented to determine the scattering coefficient mu' s from backscattered polarized images of turbid media. It uses the ratio, pixel by pixel, of two images that are the second and the first backscattered Stokes parameter images Q and I, respectively. Taking this image ratio, then integrating it over the azimuth angle, we get a function depending on the distance from the light entrance point. This function has a maximum. Using Monte Carlo simulations, for a fixed reduced scattering coefficient mu s and for an anisotropy factor g varying between 0 and 0.8, it is found a linear relationship between the scattering coefficient mu s and the inverse of the maximum position of this function.

Algorithms↗