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Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers

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Computational modeling of optical projection tomographic microscopy using the finite difference time domain method.

Ryan L Coe¹, Eric J Seibel

¹Department of Bioengineering, University of Washington, Human Photonics Laboratory, Fluke Hall, Seattle, Washington 98195, USA. ryancoe@uw.edu

Journal of the Optical Society of America. A, Optics, Image Science, and Vision

|March 5, 2013

Summary

We developed a model for optical projection tomographic microscopy (OPTM) to simulate 3D image formation. This method aids in optimizing imaging parameters for clearer cell reconstructions.

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Area of Science:

Microscopy
Optical Imaging
Computational Biology

Background:

Optical Projection Tomographic Microscopy (OPTM) reconstructs 3D cell structures from 2D projections.
High numerical aperture (NA) components are crucial for OPTM resolution.
Accurate modeling is needed to understand and improve OPTM performance.

Purpose of the Study:

To present a computational model for simulating image formation in OPTM.
To analyze the impact of various imaging parameters on 3D image reconstruction.
To provide a foundation for optimizing OPTM system design.

Main Methods:

Developed a simulation model for OPTM image formation.
Incorporated axial scanning of microscope objectives to generate projections.
Utilized filtered backprojection for image reconstruction.
Modeled optical scattering in transmission microscopy.

Main Results:

Simulated the effect of condenser NA, objective scan range, and refractive index on microshell reconstruction.
Demonstrated the model's capability to analyze critical OPTM imaging factors.
Identified key parameters influencing the quality of reconstructed 3D images.

Conclusions:

The developed model is a foundational tool for optimizing OPTM parameters.
This work paves the way for improved OPTM system design and performance.
Future expansion of the model will enable simulation of more complex biological samples.