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Proceedings Paper

Developing handheld real time multispectral imager to clinically detect erythema in darkly pigmented skin
Author(s): Linghua Kong; Stephen Sprigle; Dingrong Yi; Fengtao Wang; Chao Wang; Fuhan Liu
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Paper Abstract

Pressure ulcers have been identified as a public health concern by the US government through the Healthy People 2010 initiative and the National Quality Forum (NQF). Currently, no tools are available to assist clinicians in erythema, i.e. the early stage pressure ulcer detection. The results from our previous research (supported by NIH grant) indicate that erythema in different skin tones can be identified using a set of wavelengths 540, 577, 650 and 970nm. This paper will report our recent work which is developing a handheld, point-of-care, clinicallyviable and affordable, real time multispectral imager to detect erythema in persons with darkly pigmented skin. Instead of using traditional filters, e.g. filter wheels, generalized Lyot filter, electrical tunable filter or the methods of dispersing light, e.g. optic-acoustic crystal, a novel custom filter mosaic has been successfully designed and fabricated using lithography and vacuum multi layer film technologies. The filter has been integrated with CMOS and CCD sensors. The filter incorporates four or more different wavelengths within the visual to nearinfrared range each having a narrow bandwidth of 30nm or less. Single wavelength area is chosen as 20.8μx 20.8μ. The filter can be deposited on regular optical glass as substrate or directly on a CMOS and CCD imaging sensor. This design permits a multi-spectral image to be acquired in a single exposure, thereby providing overwhelming convenience in multi spectral imaging acquisition.

Paper Details

Date Published: 24 February 2010
PDF: 13 pages
Proc. SPIE 7557, Multimodal Biomedical Imaging V, 75570G (24 February 2010); doi: 10.1117/12.843943
Show Author Affiliations
Linghua Kong, Georgia Institute of Technology (United States)
Stephen Sprigle, Georgia Institute of Technology (United States)
Dingrong Yi, Georgia Institute of Technology (United States)
Fengtao Wang, Georgia Institute of Technology (United States)
Chao Wang, Georgia Institute of Technology (United States)
Fuhan Liu, Georgia Institute of Technology (United States)


Published in SPIE Proceedings Vol. 7557:
Multimodal Biomedical Imaging V
Fred S. Azar; Xavier Intes, Editor(s)

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