MRI-coupled fluorescence tomography of small animals:

Follow this tutorial with the associated sample data to generate MRI-FMT images of a tumor xenograph from start-to-finish: Load MRI DICOMS, place sources and detectors, segment the tissue into regions, create a 3-D mesh, calibrate and reconstruct data, and visualise optical images overlaid on MR images.

MRI-coupled NIR spectral imaging of human breast:

This exercise uses a sample MRI stack to segment the tissue and create a 3-D mesh. It also includes an exercise for completing multi-spectral reconstructions on a 2-D breast mesh.

Human head models to generate spectroscopic data and simple parameter recovery:

This tutorial allows you to create FEM meshes based on a pre-segmented head model . Alternatively, NIRFAST mesh files have been created together with a single source and three detectors on the forehead . Two different matlab script files demonstrate how we can use basic scripts to generate data, calculate the Jacobian and recover Parameters .

Basic tutorial for tomographic imaging and simulations. The script file standard_example.m outlines the simulation of data for a simple 2-D circle at a single wavelength and tomographic reconstruction. The script file spectral_example.m outlines the simulation of data for a simple 2-D circle at multiple wavelengths simultaneously and tomographic reconstruction.

Introduction to NIRFAST:

These are the slides used at the OSA 2016 workshop that introduces the historical development of NIRFAST, plus some of the basic information including the utilised file formats for NIRFAST.

Using NIRFASTSlicer: Image processing and visualisation in NIRFAST:

NIRFASTSlicer, built on the 3DSlicer platform, is the image processing and visualisation front-end for NIRFAST. This tutorial covers the basic structure, functions and use of NIRFASTSlicer and includes contextual background on the 3DSlicer project and extensions.

Tutorial: MRI-coupled fluorescence tomography of small animals:

Follow this tutorial with the associated sample data to generate MRI-FMT images of a tumor xenograph from start-to-finish: Load MRI DICOMS, place sources and detectors, segment the tissue into regions, create a 3-D mesh, calibrate and reconstruct data, and visualise optical images overlaid on MR images.

Tutorial: MRI-coupled NIR spectral imaging of human breast:

This exercise uses a sample MRI stack to segment the tissue and create a 3-D mesh. It also includes an exercise for completing multi-spectral reconstructions on a 2-D breast mesh.

Using NIRFASTSlicer: Image processing and visualisation in NIRFAST:

NIRFASTSlicer, built on the 3DSlicer platform, is the name of the new image processing and visualisation front-end for NIRFAST. This tutorial covers the basic structure, functions and use of NIRFASTSlicer and includes contextual background on the 3DSlicer project and extensions.