Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
464-01-003 ISMRM Abstract

The Impact of Denoising and Artifact Correction Pipelines on Apparent Diffusion Coefficient Quantification in Prostate MRI

Primary: Diffusion - Diffusion Analysis & Visualization
Secondary: Body - Prostate
464-01-003 · Diffusion MRI Analysis · Tuesday, 12 May, 8:20 AM–9:15 AM · Digital Posters Row E
Keywords: Quantitative MRI Diffusion-Weighted Imaging Prostate MRI Apparent diffusion coefficient Diffusion MRI Preprocessing
Accepted
Catherine J Liang1, Jiayao Yang 2, Yun Jiang1,3
1Department of Biomedical Engineering, University of Michigan, Ann Arbor, United States of America
2Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, United States of America
3Department of Radiology, University of Michigan, Ann Arbor, United States of America
Presenting Author: Jiayao Yang

Synopsis

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References

1. Turkbey B. et al., “Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2,” European Urology, vol. 76, no. 3, pp. 340-351, Sept. 2019, doi: 10.1016/j.eururo.2019.02.033. [doi]
2. Garyfallidis, E. et al., “Dipy, a library for the analysis of diffusion MRI data,” Frontiers in Neuroinformatics, vol. 8, art. 8, Feb. 2014, doi: 10.3389/fninf.2014.00008. [doi]
3. 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]
4. Kanakis et al., "The effect of diffusion MRI preprocessing on ADC estimates in prostate cancer patients." (2025).
5. R. Tibrewala et al., “FastMRI Prostate: A public, biparametric MRI dataset to advance machine learning for prostate cancer imaging,” Scientific Data, vol. 11, art. no. 404, 2024, doi: 10.1038/s41597-024-03252-w. [doi]
6. D. C. Van Essen et al., “The Human Connectome Project: a data acquisition perspective,” NeuroImage, vol. 62, no. 4, pp. 2222-2231, Oct. 2012, doi: 10.1016/j.neuroimage.2012.02.018. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/464-01-003