1. Articles from Seung Il Kim

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    1. Intraoperative margin assessment of human breast tissue in optical coherence tomography images using deep neural networks

      Intraoperative margin assessment of human breast tissue in optical coherence tomography images using deep neural networks

      Objective: In this work, we perform margin assessment of human breast tissue from optical coherence tomography (OCT) images using deep neural networks (DNNs). This work simulates an intraoperative setting for breast cancer lumpectomy. Methods: To train the DNNs, we use both the state-of-the-art methods (Weight Decay and DropOut) and a newly introduced regularization method based on function norms. Commonly used methods can fail when only a small database is available. The use of a function norm introduces a direct control over the complexity of the function with the aim of diminishing the risk of overfitting. Results: As neither the code ...

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  2. Topics in the News

    1. (1 articles) K. U. Leuven
    2. (1 articles) Sungkyunkwan University
    3. (1 articles) Chulmin Joo
    4. (1 articles) Medical University of Vienna
    5. (1 articles) Harvard University
    6. (1 articles) NYU Langone Medical Center
    7. (1 articles) Massachusetts General Hospital
    8. (1 articles) Tianjin University
    9. (1 articles) University of Hong Kong
    10. (1 articles) Semmelweis University
    11. (1 articles) Guillermo J. Tearney
    12. (1 articles) Arnaud Dubois
    13. (1 articles) Ursula Schmidt-Erfurth
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