Kidney edge detection in laparoscopic image data for computer-assisted surgery
In robotic-assisted kidney surgery, computational methods make it possible to augment the surgical scene and potentially improve patient outcome. Most often, soft-tissue registration is a prerequisite for the visualization of tumors and vascular structures hidden beneath the surface. State-of-the-ar...
Gespeichert in:
| Hauptverfasser: | , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2020
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| In: |
International journal of computer assisted radiology and surgery
Year: 2019, Jahrgang: 15, Heft: 3, Pages: 379-387 |
| ISSN: | 1861-6429 |
| DOI: | 10.1007/s11548-019-02102-0 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1007/s11548-019-02102-0
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| Verfasserangaben: | Georges Hattab, Marvin Arnold, Leon Strenger, Max Allan, Darja Arsentjeva, Oliver Gold, Tobias Simpfendörfer, Lena Maier-Hein, Stefanie Speidel |
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| 520 | |a In robotic-assisted kidney surgery, computational methods make it possible to augment the surgical scene and potentially improve patient outcome. Most often, soft-tissue registration is a prerequisite for the visualization of tumors and vascular structures hidden beneath the surface. State-of-the-art volume-to-surface registration methods, however, are computationally demanding and require a sufficiently large target surface. To overcome this limitation, the first step toward registration is the extraction of the outer edge of the kidney. | ||
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