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Model Mie scattering and light propagation through a high scattering medium using Monte Carlo simulation

Project Information

data handling, Simulations, Monte Carlo, scheduling, programming, matlab
Project Status: In Progress
Project Region: CAREERS
Submitted By: Binlin Wu
Project Email: wub1@southernct.edu
Project Institution: Southern Connecticut State University
Anchor Institution: CR-Yale
Project Address: 501 Crescent Street, SCI/ASB 045
New Haven, Connecticut. 06515

Mentors: Thomas Langford
Students: Joseph Neumann

Project Description

In this project, we will first use numerical approaches to model light scattering off single particles using Monte Carlo simulation. We will obtain results that follow Rayleigh scattering and Mie scattering. The program will then be extended to simulate light propagation in a highly scattering turbid medium like biological tissue which consists of various arrangements of particles and bulk geometry and calculate the light distribution in the medium and on the boundary. The program will eventually be used for imaging tumors in biological tissue, which will be achieved through an inverse problem.

Project Information

data handling, Simulations, Monte Carlo, scheduling, programming, matlab
Project Status: In Progress
Project Region: CAREERS
Submitted By: Binlin Wu
Project Email: wub1@southernct.edu
Project Institution: Southern Connecticut State University
Anchor Institution: CR-Yale
Project Address: 501 Crescent Street, SCI/ASB 045
New Haven, Connecticut. 06515

Mentors: Thomas Langford
Students: Joseph Neumann

Project Description

In this project, we will first use numerical approaches to model light scattering off single particles using Monte Carlo simulation. We will obtain results that follow Rayleigh scattering and Mie scattering. The program will then be extended to simulate light propagation in a highly scattering turbid medium like biological tissue which consists of various arrangements of particles and bulk geometry and calculate the light distribution in the medium and on the boundary. The program will eventually be used for imaging tumors in biological tissue, which will be achieved through an inverse problem.