Name
Abstract | ||
|---|---|---|
Fluorescence tomography of tissues has been generally limited to systems that require fixed geometries or measurements employing fibers. Certain technological advances however, have more recently allowed the development of complete-projection 360° tomographic approaches using non-contact detection and illumination. Employing multiple illumination projections and CCD cameras as detection devices vastly increases the information content acquired, posing non-trivial computational and experimental requirements. In this paper, we use singular-value analysis to optimize experimental parameters relevant to the design and operation of emerging 360° fluorescence molecular tomography (FMT) methods and systems for small animal imaging. We present the theoretical and experimental methodology, optimization results and their experimental validation. We further discuss how these results can be employed to improve the performance of existing FMT systems and guide the design of new systems. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.media.2007.04.003 | Medical Image Analysis |
Keywords | Field | DocType |
Fluorescence molecular tomography,Singular-value analysis | Computer vision,Pattern recognition,Tomography,Artificial intelligence,Animal imaging,Mathematics,Fluorescence molecular tomography | Journal |
Volume | Issue | ISSN |
11 | 4 | 1361-8415 |
Citations | PageRank | References |
10 | 1.30 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tobias Lasser | 1 | 97 | 16.81 |
| Vasilis Ntziachristos | 2 | 165 | 36.56 |