An advanced hyper-spectral imaging (HSI) system has been developed having obvious applications for cancer detection. This HSI system is based on state-of-the-art liquid crystal tunable filter technology coupled to an endoscope. The goal of this unique HSI technology being developed is to obtain spatially resolved images of the slight differences in luminescent properties of malignant versus non-malignant tissues. In this report, the development of the instrument is discussed and the capability of the instrument is demonstrated by observing mouse carcinomas in-vivo. It is shown that the instrument successfully distinguishes between normal and malignant mouse skin. It is hoped that the results of this study will lead to advances in the optical diagnosis of cancer in humans.
This paper presents a hyperspectral imaging technique based on laser‐induced fluorescence for non‐invasive detection of tumorous tissue on mouse skin. Hyperspectral imaging sensors collect image data in a number of narrow, adjacent spectral bands. Such high‐resolution measurement of spectral information reveals contiguous emission spectra at each image pixel useful for the characterization of constituent materials. The hyperspectral image data used in this study are fluorescence images of mouse skin consisting of 21 spectral bands in the visible spectrum of the wavelengths ranging from 440 nm to 640 nm. Fluorescence signal is measured with the use of laser excitation at 337 nm. An acousto‐optic tunable filter (AOTF) is used to capture images at 10 nm intervals. All spectral band images are spatially registered with the reference band image at 490 nm to obtain exact pixel correspondences by compensating the spatial offsets caused by the refraction differences in AOTF at different wavelengths during the image capture procedure. The unique fluorescence spectral signatures demonstrate a good separation to differentiate malignant tumors from normal tissues for rapid detection of skin cancers without biopsy.
Although conventional autofluorescence spectroscopy, in which fluorescence emission spectra are recorded for fixed excitation wavelengths, has demonstrated good performance in tissue diagnosis, it suffers from prolonged data acquisition time and broad-band fluorescence features. Synchronous spectroscopy has been proposed to overcome the limitations of conventional fluorescence spectroscopy but has not been applied to imaging for tissue diagnosis in vivo. Our group has developed a synchronous fluorescence imaging system to combine the great diagnostic potential of synchronous spectroscopy and the large field of view of imaging for cancer diagnosis. This system has been tested in a mouse skin model to capture synchronous fluorescence images. A simple discriminant analysis method and a more complicated multi-variate statistical method have been developed to generate a single diagnostic image from a large number of raw fluorescence images. Moreover, it was demonstrated that the diagnostic image generated from synchronous data is comparable to that generated from full spectral data in classification accuracy.
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