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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chelvam, Venkatesh | en_US |
dc.date.accessioned | 2022-03-17T01:00:00Z | - |
dc.date.accessioned | 2022-03-21T11:33:12Z | - |
dc.date.available | 2022-03-17T01:00:00Z | - |
dc.date.available | 2022-03-21T11:33:12Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | Gaind, V., Tsai, H. -., Webb, K. J., Chelvam, V., & Low, P. S. (2013). Small animal optical diffusion tomography with targeted fluorescence. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 30(6), 1146-1154. doi:10.1364/JOSAA.30.001146 | en_US |
dc.identifier.issn | 1084-7529 | - |
dc.identifier.other | EID(2-s2.0-84878546964) | - |
dc.identifier.uri | https://doi.org/10.1364/JOSAA.30.001146 | - |
dc.identifier.uri | https://dspace.iiti.ac.in/handle/123456789/9455 | - |
dc.description.abstract | Despite the broad impact in medicine that optics can bring, thus far practical approaches are limited to weak scatter or near-surface monitoring. We show a method that utilizes a laser topography scan and a diffusion equation model to describe the photon transport, together with a multiresolution unstructured grid solution to the nonlinear optimization measurement functional, that overcomes these limitations. We conclude that it is possible to achieve whole body optical imaging with a resolution suitable for finding cancer nodules within an organ during surgery, with the aid of a targeted imaging agent. © 2013 Optical Society of America. | en_US |
dc.language.iso | en | en_US |
dc.publisher | OSA - The Optical Society | en_US |
dc.source | Journal of the Optical Society of America A: Optics and Image Science, and Vision | en_US |
dc.subject | Optics | en_US |
dc.subject | Diffusion-equation models | en_US |
dc.subject | Multi-resolutions | en_US |
dc.subject | Non-linear optimization | en_US |
dc.subject | Optical diffusion tomography | en_US |
dc.subject | Optical imaging | en_US |
dc.subject | Photon transport | en_US |
dc.subject | Targeted imaging | en_US |
dc.subject | Unstructured grid | en_US |
dc.subject | Partial differential equations | en_US |
dc.subject | algorithm | en_US |
dc.subject | animal | en_US |
dc.subject | article | en_US |
dc.subject | Bayes theorem | en_US |
dc.subject | equipment | en_US |
dc.subject | finite element analysis | en_US |
dc.subject | fluorescence | en_US |
dc.subject | image processing | en_US |
dc.subject | image quality | en_US |
dc.subject | kidney | en_US |
dc.subject | laser | en_US |
dc.subject | methodology | en_US |
dc.subject | mouse | en_US |
dc.subject | neoplasm | en_US |
dc.subject | optical tomography | en_US |
dc.subject | optics | en_US |
dc.subject | pathology | en_US |
dc.subject | photon | en_US |
dc.subject | radiation scattering | en_US |
dc.subject | reproducibility | en_US |
dc.subject | surface property | en_US |
dc.subject | three dimensional imaging | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Animals | en_US |
dc.subject | Bayes Theorem | en_US |
dc.subject | Finite Element Analysis | en_US |
dc.subject | Fluorescence | en_US |
dc.subject | Image Processing, Computer-Assisted | en_US |
dc.subject | Imaging, Three-Dimensional | en_US |
dc.subject | Kidney | en_US |
dc.subject | Lasers | en_US |
dc.subject | Mice | en_US |
dc.subject | Neoplasms | en_US |
dc.subject | Optics and Photonics | en_US |
dc.subject | Phantoms, Imaging | en_US |
dc.subject | Photons | en_US |
dc.subject | Reproducibility of Results | en_US |
dc.subject | Scattering, Radiation | en_US |
dc.subject | Surface Properties | en_US |
dc.subject | Tomography, Optical | en_US |
dc.title | Small animal optical diffusion tomography with targeted fluorescence | en_US |
dc.type | Journal Article | en_US |
Appears in Collections: | Department of Chemistry |
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