Hyperspectral imaging for early diagnosis of diseases: A review

Abstract

Hyperspectral Imaging (HSI) has grown to be one of the most crucial optical imaging modalities with applications in numerous industries. The non-invasive nature of HSI has led to widening its horizon to the medical domain, especially in areas like early diagnosis of various diseases. HSI combines both imaging and spectroscopy properties, thereby exploiting spectral and spatial dimensions of images captured, providing quick and accurate interpretation of data. The current study aims to give an exhaustive overview of HSI's applications pertaining to the medical industry for fast detection of diseases and aiding in surgical procedures. The survey focuses on hyperspectral imaging combined with various approaches - machine learning, deep learning, genetic algorithms, and anomaly detection for the treatment of disorders. In addition, the survey highlights accompanying pre-processing approaches, performance metrics, inferences, and future prospects of HSI in the medical domain. The current study can gauge computer vision specialists, researchers in machine and deep learning domain, doctors, and scientists by giving them a platform for improving existing treatment methods for the betterment of society.