van Eijnatten M - Search Results

1

A cone-beam X-ray computed tomography data collection designed for machine learning.

Der Sarkissian H, Lucka F, van Eijnatten M, Colacicco G, Coban SB, Batenburg KJ. Der Sarkissian H, et al. Among authors: van eijnatten m. Sci Data. 2019 Oct 22;6(1):215. doi: 10.1038/s41597-019-0235-y. Sci Data. 2019. PMID: 31641152 Free PMC article.

2

Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications.

Leuschner J, Schmidt M, Ganguly PS, Andriiashen V, Coban SB, Denker A, Bauer D, Hadjifaradji A, Batenburg KJ, Maass P, van Eijnatten M. Leuschner J, et al. Among authors: van eijnatten m. J Imaging. 2021 Mar 2;7(3):44. doi: 10.3390/jimaging7030044. J Imaging. 2021. PMID: 34460700 Free PMC article.

3

Comparison of convolutional neural network training strategies for cone-beam CT image segmentation.

Minnema J, Wolff J, Koivisto J, Lucka F, Batenburg KJ, Forouzanfar T, van Eijnatten M. Minnema J, et al. Among authors: van eijnatten m. Comput Methods Programs Biomed. 2021 Aug;207:106192. doi: 10.1016/j.cmpb.2021.106192. Epub 2021 May 20. Comput Methods Programs Biomed. 2021. PMID: 34062493 Free article.

4

Efficient high cone-angle artifact reduction in circular cone-beam CT using deep learning with geometry-aware dimension reduction.

Minnema J, van Eijnatten M, der Sarkissian H, Doyle S, Koivisto J, Wolff J, Forouzanfar T, Lucka F, Batenburg KJ. Minnema J, et al. Among authors: van eijnatten m. Phys Med Biol. 2021 Jul 1;66(13). doi: 10.1088/1361-6560/ac09a1. Phys Med Biol. 2021. PMID: 34107467

5

3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning.

van Eijnatten M, Rundo L, Batenburg KJ, Lucka F, Beddowes E, Caldas C, Gallagher FA, Sala E, Schönlieb CB, Woitek R. van Eijnatten M, et al. Comput Methods Programs Biomed. 2021 Sep;208:106261. doi: 10.1016/j.cmpb.2021.106261. Epub 2021 Jul 8. Comput Methods Programs Biomed. 2021. PMID: 34289437 Free article.

6

Segmentation of dental cone-beam CT scans affected by metal artifacts using a mixed-scale dense convolutional neural network.

Minnema J, van Eijnatten M, Hendriksen AA, Liberton N, Pelt DM, Batenburg KJ, Forouzanfar T, Wolff J. Minnema J, et al. Among authors: van eijnatten m. Med Phys. 2019 Nov;46(11):5027-5035. doi: 10.1002/mp.13793. Epub 2019 Sep 13. Med Phys. 2019. PMID: 31463937 Free PMC article.

7

A review on the application of deep learning for CT reconstruction, bone segmentation and surgical planning in oral and maxillofacial surgery.

Minnema J, Ernst A, van Eijnatten M, Pauwels R, Forouzanfar T, Batenburg KJ, Wolff J. Minnema J, et al. Among authors: van eijnatten m. Dentomaxillofac Radiol. 2022 Sep 1;51(7):20210437. doi: 10.1259/dmfr.20210437. Epub 2022 May 23. Dentomaxillofac Radiol. 2022. PMID: 35532946 Free PMC article. Review.

8

Virtual forensic anthropology: The accuracy of osteometric analysis of 3D bone models derived from clinical computed tomography (CT) scans.

Colman KL, de Boer HH, Dobbe JGG, Liberton NPTJ, Stull KE, van Eijnatten M, Streekstra GJ, Oostra RJ, van Rijn RR, van der Merwe AE. Colman KL, et al. Among authors: van eijnatten m, van rijn rr, van der merwe ae. Forensic Sci Int. 2019 Nov;304:109963. doi: 10.1016/j.forsciint.2019.109963. Epub 2019 Sep 24. Forensic Sci Int. 2019. PMID: 31610335

9

Influence of head positioning during cone-beam CT imaging on the accuracy of virtual 3D models.

van Eijnatten M, Wolff J, Pauwels R, Karhu K, Hietanen A, der Sarkissian H, Koivisto JH. van Eijnatten M, et al. Dentomaxillofac Radiol. 2022 Sep 1;51(7):20220104. doi: 10.1259/dmfr.20220104. Epub 2022 Jul 13. Dentomaxillofac Radiol. 2022. PMID: 35766951 Free PMC article.

10

CT image segmentation methods for bone used in medical additive manufacturing.

van Eijnatten M, van Dijk R, Dobbe J, Streekstra G, Koivisto J, Wolff J. van Eijnatten M, et al. Among authors: van dijk r. Med Eng Phys. 2018 Jan;51:6-16. doi: 10.1016/j.medengphy.2017.10.008. Epub 2017 Oct 31. Med Eng Phys. 2018. PMID: 29096986 Review.

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