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  • Jan Egger
2019

Free thoracodorsal, perforator-scapular flap based on the angular artery (TDAP-Scap-aa): Clinical experiences and description of a novel technique for single flap reconstruction of extensive oromandibular defects

Pau, M., Wallner, J., Feichtinger, M., Schwaiger, M., Egger, J., Cambiaso-Daniel, J., Winter, R., Jakse, N. & Zemann, W., 2019, In : Journal of Cranio-Maxillofacial Surgery. 47, 10, p. 1617-1625

Research output: Contribution to journalArticleResearchpeer-review

Learning from the Truth: Fully Automatic Ground Truth Generation for Training of Medical Deep Learning Networks

Gsaxner, C., Roth, P. M., Wallner, J. & Egger, J., 2019, Proceedings of the Joint ARW & OAGM Workshop 2019. Pichler, A., Roth, P. M., Slabatnig, R., Stübl, G. & Vincze, M. (eds.). Graz: Verlag der Technischen Universität Graz, p. 173-174

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Open Access

Markerless Image-to-Face Registration for Untethered Augmented Reality in Head and Neck Surgery

Gsaxner, C., Pepe, A., Schmalstieg, D., Egger, J. & Wallner, J., 2019, International Conference on Medical Image Computing and Computer-Assisted Intervention. p. 236-244

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Pattern Recognition and Mixed Reality for Computer-Aided Maxillofacial Surgery and Oncological Assessment

Pepe, A., Trotta, G. F., Gsaxner, C., Schmalstieg, D., Wallner, J., Egger, J. & Bevilacqua, V., 2019, BMEiCON 2018 - 11th Biomedical Engineering International Conference. 8609921

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

PET-Train: Automatic Ground Truth Generation from PET Acquisitions for Urinary Bladder Segmentation in CT Images using Deep Learning

Gsaxner, C., Pfarrkirchner, B., Lindner, L., Pepe, A., Roth, P. M., Wallner, J. & Egger, J., 2019.

Research output: Contribution to conferencePaperResearchpeer-review

Using Synthetic Training Data for Deep Learning-Based GBM Segmentation

Lindner, L., Narnhofer, D., Weber, M., Gsaxner, C., Egger, J. & Kolodziej, M., 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Institute of Electrical and Electronics Engineers, p. 6724-6729 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2020

A comprehensive Workflow and Framework for immersive Virtual Endoscopy of dissected Aortae from CTA Data

Egger, J., Gunacker, S., Pepe, A., Melito, G. M., Gsaxner, C., Li, J., Ellermann, K. & Chen, X., 2020, Proceedings SPIE: Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling. Vol. 11315.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

IRIS: interactive real-time feedback image segmentation with deep learning

Pepe, A., Schussnig, R., Li, J., Gsaxner, C., Chen, X., Fries, T. P. & Egger, J., 2020.

Research output: Contribution to conferencePaperResearchpeer-review