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Creators/Authors contains: "Rubinstein, Gennady"

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  1. ; ; ; ; ; ; ; ; ; ; 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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  2. ; ; ; ; ; ; ; ; ; ; et al (, SPIE Optics and Photonics Conference)
    Volpe, Giovanni; Pereira, Joana B.; Brunner, Daniel; Ozcan, Aydogan (Ed.)
    Reflectance confocal microscopy (RCM) can provide in vivo images of the skin with cellular-level resolution; however, RCM images are grayscale, lack nuclear features and have a low correlation with histology. We present a deep learning-based virtual staining method to perform non-invasive virtual histology of the skin based on in vivo, label-free RCM images. This virtual histology framework revealed successful inference for various skin conditions, such as basal cell carcinoma, also covering distinct skin layers, including epidermis and dermal-epidermal junction. This method can pave the way for faster and more accurate diagnosis of malignant skin neoplasms while reducing unnecessary biopsies. 
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  3. ; ; ; ; ; ; ; ; ; ; et al (, Optica Conference on Lasers and Electro-Optics (CLEO))
    We reportin vivovirtual histology of skin without a biopsy, where deep learning is used to virtually stain tissue and generate hematoxylin and eosin (H&E)-like microscopic images of skin using a reflectance confocal microscope. 
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