Abstract
Blood oxygenation mapping by the means of optical oximetry is of significant importance in clinical trials. This paper uses hyperspectral imaging technology to obtain in vivo images for blood oxygenation detection. The experiment involves dorsal skin fold window chamber preparation which was built on adult (8–10 weeks of age) female BALB/c nu/nu mice and in vivo image acquisition which was performed by hyperspectral imaging system. To get the accurate spatial and spectral information of targets, an automatic registration scheme is proposed. An adaptive feature detection method which combines the local threshold method and the level-set filter is presented to extract target vessels. A reliable feature matching algorithm with the correlative information inherent in hyperspectral images is used to kick out the outliers. Then, the registration images are used for blood oxygenation mapping. Registration evaluation results show that most of the false matches are removed and the smooth and concentrated spectra are obtained. This intensity invariant feature detection with outliers-removing feature matching proves to be effective in hyperspectral vessel image registration. Therefore, in vivo hyperspectral imaging system by the assistance of the proposed registration scheme provides a technique for blood oxygenation research.
Highlights
The study of blood oxygenation proves to be fundamental in clinical trials involving oncology, clinicoroentgenologic, and phototherapy [1]
In order to utilize the spectral information for blood oxygen saturation analysis, we proposed a registration scheme specific for in vivo hyperspectral images
With the installation of the dorsal skin fold window chamber (DSFC) model, many researchers have paid special attention to microvasculature oxygen saturation analysis. Most of these relevant studies focus on the spatial information instead of spectral information
Summary
The study of blood oxygenation proves to be fundamental in clinical trials involving oncology, clinicoroentgenologic, and phototherapy [1]. Hyperspectral imaging technology containing sufficient spectral information may provide reliable methods for in vivo images of oxygen saturation analysis. The accuracy and stability is declining with the increase of outliers so that many research have been done to enhance resistance to the massive outliers, such as the combination of RANSAC and a Huber kernel [27], the fast sample consensus (FSC) [18] and prior energy function (P-RANSAC) [28] Most of these studies mainly focus on the spatial information contained in a single image to find the correct matching points, whereas seldom concern the correlative information in the multispectral bands. In order to utilize the spectral information for blood oxygen saturation analysis, we proposed a registration scheme specific for in vivo hyperspectral images. The clean and accurate spectrum of mice’s vessel can be obtained and used to perform the oxygen saturation analysis
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