Image-guided Tissue Spectroscopy and Image Reconstruction using NIRFAST: A hands-on course (SC1088)Course Level: Introductory
This course will teach near-infrared light propagation modeling and image reconstruction in tissue using the freely distributed NIRFAST software package. NIRFAST is a widely-used, user-friendly package for modeling NIR light propagation in tissue and recovering images of optical parameters in arbitrarily-shaped tissue volumes. This course will use a combination of instructor lecturing and hands-on exercises to teach both conceptual and practical aspects of NIR imaging using the software. Attendees will be running and visualizing light propagation models within minutes and will also practice using image reconstruction algorithms for volumetric imaging of functional parameters such as hemoglobin concentration, oxygen saturation, water content, scattering parameters, as well as fluorescence and bioluminescence activity. The class will review the basic physics and biology of the approach, step through how the software works, and train attendees how to use the software through user exercises. More information about NIRFAST can be found at <a href="http://www.nirfast.org">http://www.nirfast.org</a>
This course will enable you to:
- model multi-spectral and luminescent diffuse light propagation in any 2-D or 3-D geometry.
- use inversion techniques to recover volumetric images of optical parameters, functional parameters, and luminescence activity from simulated and experimental data
- perform multi-modal imaging by importing DICOM images from any conventional imaging device and using those images to guide the recovery of optical parameters
- become familiar with NIRFAST's user-friendly GUI interface and work with the authors of the code on your own optical imaging problems
This material is intended for biomedical engineers and medical physicists interested in medical applications of diffusive imaging applications or interested in learning more about NIRFAST and finite element modeling. Prior experience with MATLAB is beneficial.
Hamid Dehghani PhD. is author of the NIRFAST package and is currently Senior Lecturer at the University of Birmingham in the School of Computer Science and Assistant Professor of Engineering at Dartmouth College. He has published widely on image reconstruction in alternative imaging modalities.
Brian Pogue PhD. is Professor of Engineering at Dartmouth College, and works in diffuse optical imaging instrumentation and clinical studies. The tomography program at Dartmouth has used NIRFAST reconstruction in several published clinical studies.
Scott Davis PhD. is a Research Scientist at Dartmouth College, and has extensive experience in diffuse optical imaging instrumentation, and pre-clinical and clinical imaging studies. He has published widely on image-guided fluorescence molecular tomography and is a major contributor to the NIRFAST software.
IMPORTANT: It is ESSENTIAL that all attendees have a laptop with MATLAB installed while attending the course. Please ensure that the version of MATLAB installed can work without access to your local network. If you do not have a copy of MATLAB, please download and install a free trial version prior to the course http://www.mathworks.com.