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• W4366463303 abstract "Skin cancer, an anomalous development of skin cells in the epidermis, is among the most common types of cancer worldwide. Because of its clinical importance and to improve early diagnosis and patient management, there is an urgent need to develop noninvasive, accurate medical diagnostic tools. To this aim, light reflectance spectroscopy over the visible and near-infrared spectral range (400-1000 nm) based on a single-fiber six-around-one optical probe was applied to extract nine features used for diagnostics. These features include skewness, entropy, energy, kurtosis, scattering amplitude, and others, and are spread over each of four different spectral signatures, namely, light reflectance, absorbance, scattering profile approximation, and absorption/scattering ratio. Our preliminary studies focused on 11 adult patients with diagnoses of malignant melanoma (n = 4), basal cell carcinoma (n = 5), and squamous cell carcinoma (n = 2) in a variety of locations on the body. Measurements were taken first in vivo before surgery, at the site of the lesion and from healthy skin of the same patient, and ex vivo after surgical excision, where the lesion was rinsed in saline solution and measurements of the reflected light from the inside facing plane of the tissue were taken in the same manner. Overall, experimental results demonstrate that by examining a variety of wavebands, features, and statistical metrics, we can detect and distinguish cancer from normal tissue and different cancer subtypes. Nevertheless, discrepancies in results between in vivo and ex vivo tissue were observed and explanations for these discrepancies are discussed." @default.
• W4366463303 created "2023-04-22" @default.
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• W4366463303 date "2023-05-21" @default.
• W4366463303 modified "2023-10-17" @default.
• W4366463303 title "Single probe light reflectance spectroscopy and parameter spectrum feature extraction in experimental skin cancer detection and classification" @default.
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• W4366463303 doi "https://doi.org/10.1002/jbio.202300001" @default.
• W4366463303 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37078262" @default.
• W4366463303 hasPublicationYear "2023" @default.
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