Deep Learning-based Auto-contouring of Lymph Node Levels in Head and Neck Area

Weissmann T, Huang Y, Sommer P, Roesch J, Mansoorian S, Ayala H, Fischer S, Srinivasan AL, Haderlein M, Hecht M, Speer S, Schweizer C, Frey B, Gaipl U, Distel L, Ott O, Semrau S, Fietkau R, Bert C, Putz F (2022)

Publication Type: Conference contribution

Publication year: 2022

Journal

Strahlentherapie und Onkologie Urban & Vogel

Publisher: SPRINGER HEIDELBERG

City/Town: HEIDELBERG

Pages Range: S20-S21

Conference Proceedings Title: STRAHLENTHERAPIE UND ONKOLOGIE

Authors with CRIS profile

Thomas Weissmann Department of Radiation Oncology Yixing Huang Department of Radiation Oncology Johannes Roesch Department of Radiation Oncology Sina Mansoorian Department of Radiation Oncology Marlen Haderlein Department of Radiation Oncology Markus Hecht Department of Radiation Oncology Stefan Speer Department of Radiation Oncology Claudia Schweizer Department of Radiation Oncology Benjamin Frey Department of Radiation Oncology Udo Gaipl Department of Radiation Oncology Luitpold Distel Department of Radiation Oncology Oliver Ott Medizinische Fakultät Sabine Semrau Medizinische Fakultät Rainer Fietkau Lehrstuhl für Strahlentherapie Christoph Bert Professur für Med. Strahlenphysik Florian Putz Department of Radiation Oncology

How to cite

APA:

Weissmann, T., Huang, Y., Sommer, P., Roesch, J., Mansoorian, S., Ayala, H.,... Putz, F. (2022). Deep Learning-based Auto-contouring of Lymph Node Levels in Head and Neck Area. In STRAHLENTHERAPIE UND ONKOLOGIE (pp. S20-S21). HEIDELBERG: SPRINGER HEIDELBERG.

MLA:

Weissmann, Thomas, et al. "Deep Learning-based Auto-contouring of Lymph Node Levels in Head and Neck Area." Proceedings of the STRAHLENTHERAPIE UND ONKOLOGIE HEIDELBERG: SPRINGER HEIDELBERG, 2022. S20-S21.

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