Accounting for systematic errors in bioluminescence imaging to improve quantitative accuracy
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Authors
Colleges, School and Institutes
Abstract
Bioluminescence imaging (BLI) is a widely used pre-clinical imaging technique, but there are a number of limitations to its quantitative accuracy. This work uses an animal model to demonstrate some significant limitations of BLI and presents processing methods and algorithms which overcome these limitations, increasing the quantitative accuracy of the technique. The position of the imaging subject and source depth are both shown to affect the measured luminescence intensity. Free Space Modelling is used to eliminate the systematic error due to the camera/subject geometry, removing the dependence of luminescence intensity on animal position. Bioluminescence tomography (BLT) is then used to provide additional information about the depth and intensity of the source. A substantial limitation in the number of sources identified using BLI is also presented. It is shown that when a given source is at a significant depth, it can appear as multiple sources when imaged using BLI, while the use of BLT recovers the true number of sources present. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Details
Original language | English |
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Title of host publication | SPIE Proceedings |
Subtitle of host publication | Clinical and Preclinical Applications of Diffuse Optics I |
Publication status | Published - 16 Jul 2015 |
Event | Diffuse Optical Imaging V - Munich, Germany Duration: 23 Jun 2015 → 25 Jun 2015 |
Publication series
Name | SPIE Proceedings |
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Publisher | SPIE |
Volume | 9538 |
ISSN (Print) | 0277-786X |
Conference
Conference | Diffuse Optical Imaging V |
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Country | Germany |
City | Munich |
Period | 23/06/15 → 25/06/15 |
Keywords
- Bioluminescence Imaging (BLI), Bioluminescence Tomography (BLT), Quantitative accuracy, Free Space Modelling, Image reconstruction