A review of the medical hyperspectral imaging systems and unmixing algorithms' in biological tissues

Abstract

Hyperspectral fluorescence imaging (HFI) is a well-known technique in the medical research field and is considered a non-invasive tool for tissue diagnosis. This review article gives a brief introduction to acquisition methods, including the image preprocessing methods, feature selection and extraction methods, data classification techniques and medical image analysis along with recent relevant references. The process of fusion of unsupervised unmixing techniques with other classification methods, like the combination of support vector machine with an artificial neural network, the latest snapshot Hyperspectral imaging (HSI) and vortex analysis techniques are also outlined. Finally, the recent applications of hyperspectral images in cellular differentiation of various types of cancer are discussed.

Keywords: Breast cancer; Deep learning; Hyper-spectral image classification; Hyper-spectral imaging system; Hyper-spectral imaging techniques hyperspectral image applications; Lung cancer; Ophthalmology; Support vector machines; Unmixing algorithms.