A hyperspectral vessel image registration method for blood oxygenation mapping.
Qian WangQingli LiMei ZhouZhen SunHongying LiuYiting WangPublished in: PloS one (2017)
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.
Keyphrases
- deep learning
- high resolution
- convolutional neural network
- machine learning
- clinical trial
- blood flow
- mass spectrometry
- loop mediated isothermal amplification
- spinal cord
- type diabetes
- high speed
- randomized controlled trial
- computed tomography
- metabolic syndrome
- oxidative stress
- real time pcr
- healthcare
- health information
- high density
- neural network
- open label
- magnetic resonance
- sensitive detection
- molecular dynamics
- contrast enhanced
- photodynamic therapy