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

Aziz ul Rehman*, Shahzad Ahmad Qureshi

*Corresponding author for this work

    Research output: Contribution to journalReview articlepeer-review

    60 Citations (Scopus)

    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.

    Original languageEnglish
    Article number102165
    Pages (from-to)1-10
    Number of pages10
    JournalPhotodiagnosis and Photodynamic Therapy
    Volume33
    DOIs
    Publication statusPublished - Mar 2021

    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

    Fingerprint

    Dive into the research topics of 'A review of the medical hyperspectral imaging systems and unmixing algorithms’ in biological tissues'. Together they form a unique fingerprint.

    Cite this