ASTRO 2020 Research

Check out our research presentations at ASTRO 2020

Wednesday, Oct 28

Implementation of Deep Learning-Based Auto-Segmentation for Radiotherapy Planning Structures: A Multi-Center Workflow Study

This study evaluates the impact of implementing deep learning-based auto-segmented contour (DC) models in the radiotherapy (RT) planning clinical workflow and reports on user experience data.

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Sunday, Oct 25

Deep Learning-based Auto-Segmentation for Pelvic Organs at Risk and Clinical Target Volumes in Intracavitary High Dose Rate Brachytherapy

Development and evaluation of deep learning-based auto-segmented contour (DC) models for use in intracavitary HDR brachytherapy treatment planning.

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Expert grade contours. Automated integration with your treatment planning system. Run on your existing workstations, patient data stays local and secure.

  • | OARs and CTVs

  • Limbus Contour features a large selection of clinically validated organ and CTV contours that work right out of the box. No atlas creation or local curation of data necessary.

    Sites included: CNS, Head and Neck, Lung and Breast, Pelvis, and Prostate. MRI OARs coming soon. New structures added regularly.

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  • | Secure

  • State of the art deep learning entirely on local computers. No cloud transfer of patient data required.

    Get automatic contouring up and running in less than an hour. Scans are contoured in seconds.

    Contours exported as compliant DICOM RT-Structure files. Supports a wide variety of treatment planning systems. No plug-ins or extensions needed.

  • | Automated

  • Automatically detects when new CTs are available. The correct Template is applied and contouring begins automatically. DICOM RT-Structure Sets exported to Treatment Planning System automatically.

  • | Accurate

  • Accuracy backed by peer-reviewed research and extensive clinical validation.

    AI contours undergo routine clinical evaluation and re-training to fine tune and improve models over time. New structures are added regularly.

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