Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
301-02-001 ISMRM Abstract

Correction of Susceptibility Induced Distortions in Diffusion MRI from Neuro to Uro

Primary: Diffusion - Diffusion Reconstruction
Secondary: Interventional - MR-Guided Radiotherapy
301-02-001 · Advances in Rectum and Pelvis MRI · Monday, 11 May, 8:20 AM–10:10 AM · Hall 1A
Keywords: Brain Radiotherapy Body Diffusion MRI Distortion correction
Accepted
Cornelius Eichner 1,2, Shihan Qiu3, Radu Miron4, Yahang Li3, Nirmal Janardhanan3, Bryan Clifford5, Mahmoud Mostapha3, Mariappan Nadar3, Omar Darwish2, Thorsten Feiweier2
1Cancer Therapy Imaging, Varian, Siemens Healthineers AG, Forchheim, Germany
2Research & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany
3Digital Technology and Innovation, Siemens Healthineers, Princeton, United States of America
4Siemens Industry Software România, Brasov, Romania
5Siemens Medical Solutions, Boston, United States of America
Presenting Author: Cornelius Eichner

Synopsis

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References

1. M. A. Boss et al., “The QIBA Profile for Diffusion-Weighted MRI: Apparent Diffusion Coefficient as a Quantitative Imaging Biomarker,” Radiology, vol. 313, no. 1, p. e233055, Oct. 2024, doi: 10.1148/radiol.233055. [doi]
2. J. L. R. Andersson and S. N. Sotiropoulos, “An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging,” Neuroimage, vol. 125, pp. 1063–1078, Jan. 2016, doi: 10.1016/j.neuroimage.2015.10.019. [doi]
3. Q. Hou, C.-Z. Lu, M.-M. Cheng, and J. Feng, “Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition,” Nov. 22, 2022, arXiv: arXiv:2211.11943. doi:10.48550/arXiv.2211.11943 [doi]
4. J. Dai et al., “Deformable Convolutional Networks,” in 2017 IEEE International Conference on Computer Vision (ICCV), Venice: IEEE, Oct. 2017, pp. 764–773. doi: 10.1109/ICCV.2017.89. [doi]
5. A. Tong, G. Lemberskiy, C. Huang, K. Shanbhogue, T. Feiweier, and A. B. Rosenkrantz, “Exploratory study of geometric distortion correction of prostate diffusion‐weighted imaging using B0 map acquisition,” Magnetic Resonance Imaging, vol. 50, no. 5, pp. 1614–1619, Nov. 2019, doi: 10.1002/jmri.26751. [doi]
6. A. Dosovitskiy et al., “An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale,” 2020, arXiv. doi: 10.48550/ARXIV.2010.11929. [doi]
7. O. Ronneberger, P. Fischer, and T. Brox, “U-Net: Convolutional Networks for Biomedical Image Segmentation,” 2015, arXiv. doi: 10.48550/ARXIV.1505.04597. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/301-02-001