Paper
9 June 2011 An endoscopic structured lighting probe using spectral encoding
Neil T. Clancy, Danail Stoyanov, Guang-Zhong Yang, Daniel S. Elson
Author Affiliations +
Abstract
Recovering the three dimensional (3D) surface shape of tissues in minimally invasive surgery (MIS) is important for developing advanced image-guidance and navigation systems. Passive techniques for 3D reconstruction based on computational stereo are limited by the saliency of tissue texture and the view-dependent reflectance characteristics of the scene. Structured lighting provides a viable alternative by projecting known features onto the tissue surface. However, the correspondence problem (distinguishing individual projected features computationally) becomes difficult in tissue due to the presence of occlusions. Furthermore, miniaturisation of a light projection system for use in MIS, while maintaining the required light intensity, is a significant challenge. In this paper, a fibre-based probe is described that projects a spectrally-encoded pattern onto the target surface from its distal end. A dispersed broadband light source is used to project features of varying spectral content. The dominant wavelengths of imaged spots may be deduced from the RGB values of a standard colour camera using an algorithm that locates each colour on a chromaticity diagram. The results show that individual spots of a specified wavelength may be segmented and their centres of mass calculated, despite varying background colour. The probe has also been demonstrated on ex vivo tissue.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Neil T. Clancy, Danail Stoyanov, Guang-Zhong Yang, and Daniel S. Elson "An endoscopic structured lighting probe using spectral encoding", Proc. SPIE 8090, Novel Biophotonic Techniques and Applications, 809002 (9 June 2011); https://doi.org/10.1117/12.889981
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Cited by 8 scholarly publications.
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KEYWORDS
Tissues

RGB color model

Cameras

Image segmentation

Natural surfaces

Surgery

Light sources and illumination

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