Gsaxner C - Search Results

1

Medical deep learning-A systematic meta-review.

Egger J, Gsaxner C, Pepe A, Pomykala KL, Jonske F, Kurz M, Li J, Kleesiek J. Egger J, et al. Among authors: gsaxner c. Comput Methods Programs Biomed. 2022 Jun;221:106874. doi: 10.1016/j.cmpb.2022.106874. Epub 2022 May 11. Comput Methods Programs Biomed. 2022. PMID: 35588660 Free article. Review.

2

Fully Convolutional Mandible Segmentation on a valid Ground- Truth Dataset.

Egger J, Pfarrkirchner B, Gsaxner C, Lindner L, Schmalstieg D, Wallner J. Egger J, et al. Among authors: gsaxner c. Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:656-660. doi: 10.1109/EMBC.2018.8512458. Annu Int Conf IEEE Eng Med Biol Soc. 2018. PMID: 30440482

3

Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data.

Gsaxner C, Roth PM, Wallner J, Egger J. Gsaxner C, et al. PLoS One. 2019 Mar 5;14(3):e0212550. doi: 10.1371/journal.pone.0212550. eCollection 2019. PLoS One. 2019. PMID: 30835746 Free PMC article.

4

A Marker-Less Registration Approach for Mixed Reality-Aided Maxillofacial Surgery: a Pilot Evaluation.

Pepe A, Trotta GF, Mohr-Ziak P, Gsaxner C, Wallner J, Bevilacqua V, Egger J. Pepe A, et al. Among authors: gsaxner c. J Digit Imaging. 2019 Dec;32(6):1008-1018. doi: 10.1007/s10278-019-00272-6. J Digit Imaging. 2019. PMID: 31485953 Free PMC article.

5

A review on multiplatform evaluations of semi-automatic open-source based image segmentation for cranio-maxillofacial surgery.

Wallner J, Schwaiger M, Hochegger K, Gsaxner C, Zemann W, Egger J. Wallner J, et al. Among authors: gsaxner c. Comput Methods Programs Biomed. 2019 Dec;182:105102. doi: 10.1016/j.cmpb.2019.105102. Epub 2019 Sep 30. Comput Methods Programs Biomed. 2019. PMID: 31610359 Review.

6

Facial model collection for medical augmented reality in oncologic cranio-maxillofacial surgery.

Gsaxner C, Wallner J, Chen X, Zemann W, Egger J. Gsaxner C, et al. Sci Data. 2019 Dec 9;6(1):310. doi: 10.1038/s41597-019-0327-8. Sci Data. 2019. PMID: 31819060 Free PMC article.

7

Using Synthetic Training Data for Deep Learning-Based GBM Segmentation.

Lindner L, Narnhofer D, Weber M, Gsaxner C, Kolodziej M, Egger J. Lindner L, et al. Among authors: gsaxner c. Annu Int Conf IEEE Eng Med Biol Soc. 2019 Jul;2019:6724-6729. doi: 10.1109/EMBC.2019.8856297. Annu Int Conf IEEE Eng Med Biol Soc. 2019. PMID: 31947384

8

Detection, segmentation, simulation and visualization of aortic dissections: A review.

Pepe A, Li J, Rolf-Pissarczyk M, Gsaxner C, Chen X, Holzapfel GA, Egger J. Pepe A, et al. Among authors: gsaxner c. Med Image Anal. 2020 Oct;65:101773. doi: 10.1016/j.media.2020.101773. Epub 2020 Jul 7. Med Image Anal. 2020. PMID: 32738647 Review.

9

Augmented Reality for Head and Neck Carcinoma Imaging: Description and Feasibility of an Instant Calibration, Markerless Approach.

Gsaxner C, Pepe A, Li J, Ibrahimpasic U, Wallner J, Schmalstieg D, Egger J. Gsaxner C, et al. Comput Methods Programs Biomed. 2021 Mar;200:105854. doi: 10.1016/j.cmpb.2020.105854. Epub 2020 Nov 20. Comput Methods Programs Biomed. 2021. PMID: 33261944

10

Synthetic skull bone defects for automatic patient-specific craniofacial implant design.

Li J, Gsaxner C, Pepe A, Morais A, Alves V, von Campe G, Wallner J, Egger J. Li J, et al. Among authors: gsaxner c. Sci Data. 2021 Jan 29;8(1):36. doi: 10.1038/s41597-021-00806-0. Sci Data. 2021. PMID: 33514740 Free PMC article.

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