Delineation of the Arm Blood Vessels Utilizing Hyperspectral Imaging to Assist with Phlebotomy for Exploiting the Cutaneous Tissue Oxygen Concentration

Aref, Mohamed Hisham; Sharawi, Amr A.; El-Sharkawy, Yasser H.

doi:10.1016/j.pdpdt.2021.102190

Cited by 18 publications

(9 citation statements)

References 18 publications

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“…The use of an H2O flow model was proposed in Thiem et al, 2021's work for detecting oral malignancy by performing tissue classification. While Zarei et al, 2017 presented a methodology for automated detection of prostate glandular structures and their nuclei from a Tissue Micro Array M. H. F. Aref et al, 2021 gave a proposal for a non‐invasive custom optical imaging system for detection of arm blood vessels, both studies using K‐means for clustering and segmentation.…”

Section: Literature Review Of Hyperspectral Imaging In Medical Domainmentioning

confidence: 99%

“…M. H. Aref et al, 2020 examine the use of HSI in thermal liver ablation (ex vivo) and combine both spectral and spatial information by performing K‐means clustering after application of a moving average filter, effectively decreasing the time taken and increasing accuracy in discrimination of normal, ablated and thermal categories of tissues. In another study (M. H. F. Aref et al, 2021), K‐means is again used with a moving average filter for image segmentation to delineate oxygenated arteries and the deoxygenated veins of arm blood vessels. Sometimes the algorithm is combined with a supervised one (for example, SAM‐Spectral Angle Mapper) like in Denstedt et al, 2013's study of diagnosing chronic skin ulcers.…”

Section: Literature Review Of Hyperspectral Imaging In Medical Domainmentioning

confidence: 99%

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Hyperspectral imaging for early diagnosis of diseases: A review

et al. 2023

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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.

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Section: Literature Review Of Hyperspectral Imaging In Medical Domainmentioning

confidence: 99%

Section: Literature Review Of Hyperspectral Imaging In Medical Domainmentioning

confidence: 99%

Hyperspectral imaging for early diagnosis of diseases: A review

et al. 2023

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“…Specifically, HSI measures the intensity changes at multiple wavelengths, demonstrating the reflection, emission or fluorescence interactions with the target tissues, which indicate the changes in the biological structure of its components and changes in the concentration of intrinsic light-absorbing or luminescent chromophores. Researchers have demonstrated the ability of HSI to detect a wide range of diseases, such as oximetry of the retinal ( Gao et al, 2012 ; Hadoux et al, 2019 ; Lim et al, 2021 ), intestinal ischemia identification ( Barberio et al, 2020 ; Mehdorn et al, 2020 ), histopathological tissue analysis ( Khouj et al, 2018 ), detecting cancer metastases in lung and lymph node tissue ( Zhang et al, 2021 ), blood vessel visualization enhancement ( Bjorgan et al, 2015 ; Fouad Aref et al, 2021 ), identifying skin tumors ( Leon et al, 2020 ; Courtenay et al, 2021 ), evaluating the cholesterol levels ( Milanic et al, 2015 ), diabetic foot, etc. In the field of oncology, HSI technology has been successfully applied to detect head and neck cancer ( Halicek et al, 2017 ; Eggert et al, 2022 ), thyroid and salivary glands ( Halicek et al, 2020 ), gastric cancer ( Li et al, 2019 ; Liu et al, 2020a ), oral cancer ( Jeyaraj et al, 2020 ), colon cancer ( Baltussen et al, 2019 ; Manni, 2020 ; Maktabi, 2021 ) as well as breast cancer ( Kho et al, 2019 ; Aboughaleb et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Review on the Application of Hyperspectral Imaging Technology of the Exposed Cortex in Cerebral Surgery

Yang

et al. 2022

Front. Bioeng. Biotechnol.

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The study of brain science is vital to human health. The application of hyperspectral imaging in biomedical fields has grown dramatically in recent years due to their unique optical imaging method and multidimensional information acquisition. Hyperspectral imaging technology can acquire two-dimensional spatial information and one-dimensional spectral information of biological samples simultaneously, covering the ultraviolet, visible and infrared spectral ranges with high spectral resolution, which can provide diagnostic information about the physiological, morphological and biochemical components of tissues and organs. This technology also presents finer spectral features for brain imaging studies, and further provides more auxiliary information for cerebral disease research. This paper reviews the recent advance of hyperspectral imaging in cerebral diagnosis. Firstly, the experimental setup, image acquisition and pre-processing, and analysis methods of hyperspectral technology were introduced. Secondly, the latest research progress and applications of hyperspectral imaging in brain tissue metabolism, hemodynamics, and brain cancer diagnosis in recent years were summarized briefly. Finally, the limitations of the application of hyperspectral imaging in cerebral disease diagnosis field were analyzed, and the future development direction was proposed.

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“…The hyperspectral imaging (HSI) system is a substitution modality for biological detection and RGB imaging for its ability to segregate between various materials by utilizing both morphological and spectral characteristics [26][27][28]. This tool has been effectively employed to support the diagnosis of various types of histological samples, for example, blood oxygenation and microcirculation [29][30][31], brain cancer detection [32,32], tissue characterization [33][34][35][36][37][38], and monitoring liver ablation [39][40][41][42][43][44], and in the field of breast cancer [15,[45][46][47][48].…”

Section: Introductionmentioning

confidence: 99%

Characterization of Normal and Malignant Breast Tissues utilizing Hyperspectral Images and Associated Differential Spectrum Algorithm

Aref

Youssef

El-Sharkawy

2021

J-BPE

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Breast malignancy is the most pervasive disease and a significant reason for death in women around the world. Recently, Photonic technologies play a vital role in medical applications. This study presents an outline of recent outcomes on the magnitude of breast tissue optical properties. We established an optical system setup utilizing a hyperspectral (HS) camera with poly-chromatic source lights with wavelength (380~1050 nm) for this investigation. Measuring the diffuse reflection (Ŗd) of the investigated ex vivo breast sample to select the optimum spectral image to differentiate between the normal and tumor in the near infra-red and visible (NIR–VIS) spectrum. Finally, applying the custom algorithm to increase the image contrast and applying contour delineation of the malignant regions. The experimental analysis indicates key spectroscopic variations between normal tissue and malignant region in range (550~650 nm). Although, after data normalization, there was noticeable variation at three ranges (630–680 nm), (720–770 nm), and (830–880 nm). The calculated standard deviation (Şd) between the normal and cancer tissue to validate the selective ranges shows that the highest contrast at wavelength 680 nm. However, the histogram analysis illustrates that the spectral image at 600 nm was higher contrast and wavelength 400 nm was the lowest contrast from the select seven-spectral images (400, 500, 600, 700, 800, 900, 1000 nm) to avoid the processing time of the captured HS 128-frames. The proposed potential method could provide promising results on the investigated breast sample optical properties in the diagnostic applications to assist the pathologist and the surgeon. Where the optimum wavelength at 680 nm for diagnostic applications and the ideal spectral image at 600 nm discriminate between the normal and malignant tissue.

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Delineation of the Arm Blood Vessels Utilizing Hyperspectral Imaging to Assist with Phlebotomy for Exploiting the Cutaneous Tissue Oxygen Concentration

Cited by 18 publications

References 18 publications

Hyperspectral imaging for early diagnosis of diseases: A review

Hyperspectral imaging for early diagnosis of diseases: A review

Review on the Application of Hyperspectral Imaging Technology of the Exposed Cortex in Cerebral Surgery

Characterization of Normal and Malignant Breast Tissues utilizing Hyperspectral Images and Associated Differential Spectrum Algorithm

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