Search Results - "Giambattista, Jonathan"

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  1. 1

    Comparing deep learning-based auto-segmentation of organs at risk and clinical target volumes to expert inter-observer variability in radiotherapy planning by Wong, Jordan, Fong, Allan, McVicar, Nevin, Smith, Sally, Giambattista, Joshua, Wells, Derek, Kolbeck, Carter, Giambattista, Jonathan, Gondara, Lovedeep, Alexander, Abraham

    Published in Radiotherapy and oncology (01-03-2020)
    “…•Deep learning-based auto-segmented contours (DC) can provide significant time savings.•DCs for organs at risk accurately reproduce expert contours.•DCs for…”
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    Journal Article
  2. 2

    Implementation of deep learning-based auto-segmentation for radiotherapy planning structures: a workflow study at two cancer centers by Wong, Jordan, Huang, Vicky, Wells, Derek, Giambattista, Joshua, Giambattista, Jonathan, Kolbeck, Carter, Otto, Karl, Saibishkumar, Elantholi P, Alexander, Abraham

    Published in Radiation oncology (London, England) (08-06-2021)
    “…Purpose We recently described the validation of deep learning-based auto-segmented contour (DC) models for organs at risk (OAR) and clinical target volumes…”
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    Journal Article
  3. 3

    Training and Validation of Deep Learning-Based Auto-Segmentation Models for Lung Stereotactic Ablative Radiotherapy Using Retrospective Radiotherapy Planning Contours by Wong, Jordan, Huang, Vicky, Giambattista, Joshua A, Teke, Tony, Kolbeck, Carter, Giambattista, Jonathan, Atrchian, Siavash

    Published in Frontiers in oncology (07-06-2021)
    “…Deep learning-based auto-segmented contour (DC) models require high quality data for their development, and previous studies have typically used prospectively…”
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    Journal Article
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