Saalbach A - Search Results

1

Optimal C-arm angulation during transcatheter aortic valve replacement: Accuracy of a rotational C-arm computed tomography based three dimensional heart model.

Veulemans V, Mollus S, Saalbach A, Pietsch M, Hellhammer K, Zeus T, Westenfeld R, Weese J, Kelm M, Balzer J. Veulemans V, et al. Among authors: saalbach a. World J Cardiol. 2016 Oct 26;8(10):606-614. doi: 10.4330/wjc.v8.i10.606. World J Cardiol. 2016. PMID: 27847562 Free PMC article.

2

Optimizing GHT-based heart localization in an automatic segmentation chain.

Saalbach A, Wächter-Stehle I, Kneser R, Mollus S, Peters J, Weese J. Saalbach A, et al. Med Image Comput Comput Assist Interv. 2011;14(Pt 3):463-70. doi: 10.1007/978-3-642-23626-6_57. Med Image Comput Comput Assist Interv. 2011. PMID: 22003732

3

Automatic multi-model-based segmentation of the left atrium in cardiac MRI scans.

Kutra D, Saalbach A, Lehmann H, Groth A, Dries SP, Krueger MW, Dössel O, Weese J. Kutra D, et al. Among authors: saalbach a. Med Image Comput Comput Assist Interv. 2012;15(Pt 2):1-8. doi: 10.1007/978-3-642-33418-4_1. Med Image Comput Comput Assist Interv. 2012. PMID: 23286025

4

Limited angle C-arm tomography and segmentation for guidance of atrial fibrillation ablation procedures.

Schäfer D, Meyer C, Bullens R, Saalbach A, Eshuis P. Schäfer D, et al. Among authors: saalbach a. Med Image Comput Comput Assist Interv. 2012;15(Pt 1):634-41. doi: 10.1007/978-3-642-33415-3_78. Med Image Comput Comput Assist Interv. 2012. PMID: 23285605

5

Tubular shape aware data generation for segmentation in medical imaging.

Sirazitdinov I, Schulz H, Saalbach A, Renisch S, Dylov DV. Sirazitdinov I, et al. Among authors: saalbach a. Int J Comput Assist Radiol Surg. 2022 Jun;17(6):1091-1099. doi: 10.1007/s11548-022-02621-3. Epub 2022 Apr 17. Int J Comput Assist Radiol Surg. 2022. PMID: 35430716

6

A novel bone suppression method that improves lung nodule detection : Suppressing dedicated bone shadows in radiographs while preserving the remaining signal.

von Berg J, Young S, Carolus H, Wolz R, Saalbach A, Hidalgo A, Giménez A, Franquet T. von Berg J, et al. Among authors: saalbach a. Int J Comput Assist Radiol Surg. 2016 Apr;11(4):641-55. doi: 10.1007/s11548-015-1278-y. Epub 2015 Sep 4. Int J Comput Assist Radiol Surg. 2016. PMID: 26337439

7

Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification.

Baltruschat IM, Nickisch H, Grass M, Knopp T, Saalbach A. Baltruschat IM, et al. Among authors: saalbach a. Sci Rep. 2019 Apr 23;9(1):6381. doi: 10.1038/s41598-019-42294-8. Sci Rep. 2019. PMID: 31011155 Free PMC article.

8

Correction of Motion Artifacts Using a Multiscale Fully Convolutional Neural Network.

Sommer K, Saalbach A, Brosch T, Hall C, Cross NM, Andre JB. Sommer K, et al. Among authors: saalbach a. AJNR Am J Neuroradiol. 2020 Mar;41(3):416-423. doi: 10.3174/ajnr.A6436. Epub 2020 Feb 13. AJNR Am J Neuroradiol. 2020. PMID: 32054615 Free PMC article.

9

Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation.

Baltruschat I, Steinmeister L, Nickisch H, Saalbach A, Grass M, Adam G, Knopp T, Ittrich H. Baltruschat I, et al. Among authors: saalbach a. Eur Radiol. 2021 Jun;31(6):3837-3845. doi: 10.1007/s00330-020-07480-7. Epub 2020 Nov 21. Eur Radiol. 2021. PMID: 33219850 Free PMC article.

10

Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-ray Data.

Ziegler J, Pfitzner B, Schulz H, Saalbach A, Arnrich B. Ziegler J, et al. Among authors: saalbach a. Sensors (Basel). 2022 Jul 11;22(14):5195. doi: 10.3390/s22145195. Sensors (Basel). 2022. PMID: 35890875 Free PMC article.

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