| [179099] |
| Title: Deep learning based segmentation of cervical blood vessels in ultrasound images. <em>The European Anaesthesiology Congress, Euroanaesthesia 2022</em> |
| Written by: T. Sonntag and M. Bauer and J. Sprenger and S. Gerlach and P. Breitfeld and A. Schlaefer |
| in: <em>European journal of anaesthesiology</em>. (2022). |
| Volume: <strong>39</strong>. Number: (e-Supplement 60), |
| on pages: 41-41 |
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| ISBN: 0265-0215 |
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| URL: http://hdl.handle.net/11420/14525 |
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Abstract: Puncture of central vessels is a frequently used therapeutic and diagnostic procedure. The use of ultrasound (US) during needle insertion has become the gold standard. Handling the US probe and needle is challenging, especially in difficult anatomic conditions. Our long-term vision is a deep learning based and augmented reality (AR) assisted needle puncture. We aim to visualize the vessel structures in 3D based on 2D US image segmentation. While punctuating, the relative needle tip position and relevant vessels can be highlighted via AR lenses to optimize the image guidance process