Hyperspectral imaging for the detection of retinal disease

Harvey, Andrew R.; Lawlor, J; McNaught, Andrew; Williams, John W; Fletcher-Holmes, David William

doi:10.1117/12.451693

Cited by 23 publications

(15 citation statements)

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“…Hyperspectral imaging technologies are also being utilized in medical (Harvey, Lawlor, McNaught, & Fletcher-Holmes, 2002;Levenson, Wachman, Niu, & Farkas, 1998) biological, agricultural, and industrial areas (Heitschmidt, Lanoue, Mao, & May, 1998;Lu & Chen, 1998;Lu, Chen, Park, & Choi, 1999;Willoughby, Folkman, & Figueroa, 1996). Furthermore, this great potential hyperspectral imaging technology has been applied for food quality and safety (Hahn, 2002;Lu & Chen, 1998;Lu et al, 1999).…”

Section: Introductionmentioning

confidence: 96%

Performance of hyperspectral imaging system for poultry surface fecal contaminant detection

Park

Lawrence

Windham

et al. 2006

Journal of Food Engineering

117

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Section: Introductionmentioning

confidence: 96%

Performance of hyperspectral imaging system for poultry surface fecal contaminant detection

Park

Lawrence

Windham

et al. 2006

Journal of Food Engineering

117

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“…Early on, investigators predicted the utility of hyperspectral imaging systems for detecting early changes in retinal disease when they observed their hyperspectral device's ability to distinguish oxygenated and deoxygenated hemoglobin, and thus, discriminate retinal features such as retinal arteries, veins, and capillary beds [36] . Subsequent applications of hyperspectral systems in ophthalmology employed are able to map changes in oxygen saturation of retinal vascular structures, which is important for increasing our understanding of underlying ocular, vascular pathology, from diabetic retinopathy, arteriovenous occlusion, and glaucoma.…”

Section: Discussionmentioning

confidence: 99%

Hyperspectral imaging of retinal microvascular anatomy

Kashani

Wong

Koulisis

et al. 2015

JBEI

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Background: Hyperspectral image processing has been applied to many aspects of astronomical and earth science research. Furthermore, advances in computed tomographic imaging spectroscopy and diffraction grating design have allowed biological applications for non-invasive tissue analysis. Herein, we describe a hyperspectral computed tomographic imaging spectroscope (HCTIS) that provides high spatial, spectral and temporal resolution ideal for imaging biological tissue in vivo. Methods:We demonstrate proof-of-principle application of the HCTIS by imaging and mapping the microvascular anatomy of the retina of a model organism (rabbit) in vivo. The imaging procedure allows rapid and dense spectral sampling, is non-toxic, non-invasive, and easily adaptable to a commercially available fundus camera system.Results: HCTIS provides highly co-registered temporal, spatial and spectral data with resolution capable of reconstructing the fine vascular tree of the rabbit retina in vivo. Conclusions:We show that HCTIS allows for reliable and reproducible tissue classification and detection using signature discriminant analysis. Future applications of this system may provide promising diagnostic methods for diseases of many tissues.

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“…[5][6][7][8][9][10] A multispectral image set I͑x , y , ͒, referred to as a spectral cube or a lambda stack, contains spatial ͑pixel͒ information along two dimensions ͑x , y͒ and spectral information along the third dimension . With spectral data available at each image point x = ͑x , y͒ it is possible to derive quantitative maps of diagnostically important physiological parameters such as, for example, blood oxygenation, melanin pigmentation, and density of macular pigment.…”

Section: Introductionmentioning

confidence: 99%

Multispectral imaging of the ocular fundus using light emitting diode illumination

Everdell

Styles

Calcagni

et al. 2010

Review of Scientific Instruments

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We present an imaging system based on light emitting diode (LED) illumination that produces multispectral optical images of the human ocular fundus. It uses a conventional fundus camera equipped with a high power LED light source and a highly sensitive electron-multiplying charge coupled device camera. It is able to take pictures at a series of wavelengths in rapid succession at short exposure times, thereby eliminating the image shift introduced by natural eye movements (saccades). In contrast with snapshot systems the images retain full spatial resolution. The system is not suitable for applications where the full spectral resolution is required as it uses discrete wavebands for illumination. This is not a problem in retinal imaging where the use of selected wavelengths is common. The modular nature of the light source allows new wavelengths to be introduced easily and at low cost. The use of wavelength-specific LEDs as a source is preferable to white light illumination and subsequent filtering of the remitted light as it minimizes the total light exposure of the subject. The system is controlled via a graphical user interface that enables flexible control of intensity, duration, and sequencing of sources in synchrony with the camera. Our initial experiments indicate that the system can acquire multispectral image sequences of the human retina at exposure times of 0.05 s in the range of 500-620 nm with mean signal to noise ratio of 17 dB (min 11, std 4.5), making it suitable for quantitative analysis with application to the diagnosis and screening of eye diseases such as diabetic retinopathy and age-related macular degeneration.

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Hyperspectral imaging for the detection of retinal disease

Cited by 23 publications

References 0 publications

Performance of hyperspectral imaging system for poultry surface fecal contaminant detection

Performance of hyperspectral imaging system for poultry surface fecal contaminant detection

Hyperspectral imaging of retinal microvascular anatomy

Multispectral imaging of the ocular fundus using light emitting diode illumination

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