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

Rehman, Aziz ul; Qureshi, Shahzad Ahmad

doi:10.1016/j.pdpdt.2020.102165

Cited by 70 publications

(36 citation statements)

References 101 publications

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“…medical diagnosis [9], forensics [10] and artwork authentication [11], etc. Moreover, HSI has also been successfully applied in other image processing and machine learning tasks, such as object detection and material identification [12].…”

Section: Introductionmentioning

confidence: 99%

Nondestructive Phenolic Compounds Measurement and Origin Discrimination of Peated Barley Malt Using Near-Infrared Hyperspectral Imagery and Machine Learning

Yan

Ren

Tschannerl

et al. 2021

IEEE Trans. Instrum. Meas.

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Section: Introductionmentioning

confidence: 99%

Nondestructive Phenolic Compounds Measurement and Origin Discrimination of Peated Barley Malt Using Near-Infrared Hyperspectral Imagery and Machine Learning

Yan

Ren

Tschannerl

et al. 2021

IEEE Trans. Instrum. Meas.

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“…The sample is recorded spatially and spectrally resolved, getting a spectrum for each pixel. 38 Figure 2 depicts an example of a typical HSI spectral cube.…”

Section: Acquisition Of Hsi Datamentioning

confidence: 99%

“…51 Computer-based algorithms are applied for extraction, storage, and manipulation. 38,52 The HSI data processing workflow then consists of image acquirement, calibration, spectral, spatial preprocessing, reduction of dimensions, and detection of specific targets. Preprocessing methods aim to demonstrate image information more precisely.…”

Section: Hsi Data Processingmentioning

confidence: 99%

“…In the data preprocessing phase, noise reduction, image segmentation, image smoothness, flattening, normalization, baseline correction, and compression are used. 38,53 Removal of noise, dead pixels, spiked points, and data compression is performed after that. 54…”

Section: Hsi Data Processingmentioning

confidence: 99%

“…Thus, principle component analyses (PCA), 12,60 partial least squares (PLS), 61 Kernel PCA, 62 and a Linear Discriminant Analyser (LDA) can be used. 38…”

Section: Hsi Data Classificationmentioning

confidence: 99%

See 2 more Smart Citations

New perspectives of hyperspectral imaging for clinical research

et al. 2021

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New developments in instrumentation and data analysis have further improved the perspectives of hyperspectral imaging in clinical use. Thus, hyperspectral imaging can be considered as “Next Generation Imaging” for future clinical research. As a contactless, non-invasive method with short process times of just a few seconds, it quantifies predefined substance classes. Results of hyperspectral imaging may support the detection of carcinomas and the classification of different tissue structures as well as the assessment of tissue blood flow. Taken together, this method combines the principle of spectroscopy with imaging using conventional visual cameras. Compared to other optical imaging methods, hyperspectral imaging also analyses deeper layers of tissue.

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Research progress on the application of hyperspectral imaging techniques in tea science

Liang

Zhou

Ling

et al. 2023

Journal of Chemometrics

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Hyperspectral imaging technology combines two‐dimensional imaging and spectral technology, which can simultaneously obtain spatial and spectral information of the object to be measured and is an advanced technical method. With the development of science and technology, the detection of tea has also been continuously improved, and it has developed in the direction of being nondestructive, fast, real‐time, and accurate. In this paper, the principle of hyperspectral imaging technology is introduced, and according to research on hyperspectral imaging technology in the nondestructive rapid detection of tea in the past 5 years, the application of hyperspectral imaging technology in the detection of tea biochemical components, accurate classification, determination of mildew degree, and stress monitoring and the application progress in planting production management are analyzed. Additionally, the main challenges existing in the current research are analyzed, and future application prospects are proposed to provide a reference for the application and promotion of hyperspectral imaging technology in the actual production of tea.

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

Cited by 70 publications

References 101 publications

Nondestructive Phenolic Compounds Measurement and Origin Discrimination of Peated Barley Malt Using Near-Infrared Hyperspectral Imagery and Machine Learning

Nondestructive Phenolic Compounds Measurement and Origin Discrimination of Peated Barley Malt Using Near-Infrared Hyperspectral Imagery and Machine Learning

New perspectives of hyperspectral imaging for clinical research

Research progress on the application of hyperspectral imaging techniques in tea science

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