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Proceedings Paper

Towards a simulation framework to maximize the resolution of biomedical hyperspectral imaging
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Paper Abstract

When light is incident upon tissue, imaging contrast can be obtained from a range of interactions including absorption, scattering and fluorescence. Clinical optical imaging systems are typically optimized to report on a single contrast source, for example, using standard RGB cameras to produce white light reflectance images or filter-based approaches to extract fluorescence emissions. Hyperspectral imaging has the potential to over-come the need for specialized instrumentation, by sampling spatial and spectral information simultaneously. In particular, spectrally resolved detector arrays (SRDAs) now monolithically integrate spectral filters with CMOS image sensors to provide a robust, compact and low cost solution to video rate hyperspectral imaging. However, SRDAs suffer from a significant limitation, which is the inherent tradeoff between spatial and spectral resolution. Therefore, the properties of the SRDA including the number of filters, their wavelength and bandwidth, needs be optimized for tissue imaging. To achieve this, we have developed a software framework to optimize spectral band selection, simulating the hyperspectral sample illumination, data acquisition and spectral unmixing processes. Our approach shows early promise for selecting appropriate spectral filters, which allows us to maintain high spatial resolution for imaging.

Paper Details

Date Published: 28 July 2017
PDF: 4 pages
Proc. SPIE 10412, Diffuse Optical Spectroscopy and Imaging VI, 104120C (28 July 2017); doi: 10.1117/12.2284109
Show Author Affiliations
Travis W. Sawyer, Univ. of Cambridge (United Kingdom)
Sarah E. Bohndiek, Univ. of Cambridge (United Kingdom)


Published in SPIE Proceedings Vol. 10412:
Diffuse Optical Spectroscopy and Imaging VI
Hamid Dehghani; Heidrun Wabnitz, Editor(s)

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