Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications

Hyperspectral imaging (HSI) is an advanced spectral imaging technique that captures spatial and spectral information across numerous wavelength bands. This capability allows tissue characterization, disease detection and diagnosis, surgical guidance, and digital histopathology, making it an increasingly valuable tool with wide biological and medical applications.

We aim to provide readers with (1) an understanding of the principles and technological advancements in HSI, (2) a comprehensive overview of HSI data processing and analysis methods, and (3) an updated survey of biomedical applications, from disease detection, intraoperative imaging, to histopathology.

A systematic literature search was conducted using PubMed and Google Scholar with the keyword "hyperspectral imaging." We previously published a comprehensive review paper on medical HSI in 2014, which was widely cited in the field. Therefore, this updated review focused on new technology advancements and emerging applications. Based on their biological and medical relevance, 612 HSI papers were included and analyzed in this review.

Recent advances in HSI span both hardware and computational techniques, including improvements in sensor technology, data processing and analysis, short-wave near-infrared imaging, and deep-learning and AI tools. HSI is actively explored for various applications in oncology, neurology, ophthalmology, dermatology, cardiology, gastroenterology, hepatology, wound care, endocrinology, dentistry, infectious disease, plastic and reconstructive surgery, general surgery, intraoperative guidance, histopathology, microbiology, nanopathology, and pharmacology.

HSI has become an emerging imaging modality in biomedical research and clinical settings. Continued advancements in hardware miniaturization, computational efficiency, and clinical validation will further solidify the role of next-generation HSI in biomedicine.