1. Articles from Matin Hosseinzadeh

    1-3 of 3
    1. Universal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms

      Universal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms

      Currently, diagnosis of skin diseases is based primarily on the visual pattern recognition skills and expertise of the physician observing the lesion. Even though dermatologists are trained to recognize patterns of morphology, it is still a subjective visual assessment. Tools for automated pattern recognition can provide objective information to support clinical decision-making. Noninvasive skin imaging techniques provide complementary information to the clinician. In recent years, optical coherence tomography (OCT) has become a powerful skin imaging technique. According to specific functional needs, skin architecture varies across different parts of the body, as do the textural characteristics in OCT images. There is ...

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      Mentions: Saba Adabi
    2. Universal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms

      Universal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms

      Currently, diagnosis of skin diseases is based primarily on visual pattern recognition skills and expertise of the physician observing the lesion. Even though dermatologists are trained to recognize patterns of morphology, it is still a subjective visual assessment. Tools for automated pattern recognition can provide objective information to support clinical decision-making. Noninvasive skin imaging techniques provide complementary information to the clinician. In recent years, optical coherence tomography has become a powerful skin imaging technique. According to specific functional needs, skin architecture varies across different parts of the body, as do the textural characteristics in OCT images. There is, therefore, a ...

      Read Full Article
      Mentions: Saba Adabi
    3. Textural analysis of optical coherence tomography skin images: quantitative differentiation between healthy and cancerous tissues

      Textural analysis of optical coherence tomography skin images: quantitative differentiation between healthy and cancerous tissues

      Optical Coherence Tomography (OCT) offers real-time high-resolution three-dimensional images of tissue microstructures. In this study, we used OCT skin images acquired from ten volunteers, neither of whom had any skin conditions addressing the features of their anatomic location. OCT segmented images are analyzed based on their optical properties (attenuation coefficient) and textural image features e.g., contrast, correlation, homogeneity, energy, entropy, etc. Utilizing the information and referring to their clinical insight, we aim to make a comprehensive computational model for the healthy skin. The derived parameters represent the OCT microstructural morphology and might provide biological information for generating an atlas ...

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      Mentions: Saba Adabi
    1-3 of 3
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  2. Topics in the News

    1. (3 articles) Saba Adabi
    2. (1 articles) Jikei University School of Medicine
    3. (1 articles) Macquarie University
    4. (1 articles) Medical University of Vienna
    5. (1 articles) University of Florence
    6. (1 articles) National Institutes of Health
    7. (1 articles) Beth Israel Deaconess Medical Center
    8. (1 articles) Giacomo Savini
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