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Editors contains: "Shaked, Natan T."

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  1. ; ; (, Label-free Biomedical Imaging and Sensing (LBIS) 2023)
    Shaked, Natan T.; Hayden, Oliver (Ed.)
    Full Text Available 
  2. ; ; ; ; ; ; ; ; ; ; et al (, SPIE Photonics West)
    Shaked, Natan T.; Hayden, Oliver (Ed.)
    We report label-free, in vivo virtual histology of skin using reflectance confocal microscopy (RCM). We trained a deep neural network to transform in vivo RCM images of unstained skin into virtually stained H&E-like microscopic images with nuclear contrast. This framework successfully generalized to diverse skin conditions, e.g., normal skin, basal cell carcinoma, and melanocytic nevi, as well as distinct skin layers, including the epidermis, dermal-epidermal junction, and superficial dermis layers. This label-free in vivo skin virtual histology framework can be transformative for faster and more accurate diagnosis of malignant skin neoplasms, with the potential to significantly reduce unnecessary skin biopsies. 
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