The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): A Challenge for Reproducible DCE-MRI AI-based Analysis
Motivation: There is a need for reproducibility, repeatability, and accuracy. Previously, OSIPI organized a challenge for benchmarking DCE software. As the use of artificial intelligence grows, we now set out to repeat the challenge, focusing on deep learning techniques. Goal(s): To encourage researchers put their quantitative methods to test and stimulate collaboration and to charter the heterogeneity of DCE analysis software. Approach: To use deep learning techniques to estimate perfusion parameters in DCE-MRI of the uterus. We share repeated in-vivo data to assess the algorithm’s precision, and simulated DCE-data to test the accuracy. Results: Top three winners may present their method at ISMRM 2025. Impact: As quantitative perfusion MRI receives more importance and attention, the need for reproducibility, repeatability, and accuracy is inevitable. A public challenge within the MRI community is a great way to highlight the quantification of DCE-MRI.
Authors
- Anahita Fathi Kazerooni (ORCID: https://orcid.org/0000-0001-7131-2261)
- Oliver J. Gurney‐Champion (ORCID: https://orcid.org/0000-0003-1750-6617)
- Eve Shalom (ORCID: https://orcid.org/0000-0001-8762-3726)
- Natalie J. Serkova (ORCID: https://orcid.org/0000-0002-4573-3895)
- Henk J. M. M. Mutsaerts (ORCID: https://orcid.org/0000-0003-0894-0307)
- Rianne A. van der Heijden (ORCID: https://orcid.org/0000-0001-6964-2536)
- Safa Hoodeshenas
- Petra J. van Houdt (ORCID: https://orcid.org/0000-0001-7431-8386)
- Soudabeh Kargar (ORCID: https://orcid.org/0000-0002-8907-983X)
- Yuriko Suzuki (ORCID: https://orcid.org/0000-0002-4851-7872)
- Lucy Kershaw (ORCID: https://orcid.org/0000-0001-9510-7940)
- André Monteiro Paschoal (ORCID: https://orcid.org/0000-0001-8269-711X)
- Laura C. Bell (ORCID: https://orcid.org/0000-0001-8164-8324)
- Harrison Kim (ORCID: https://orcid.org/0000-0002-9126-1964)
- Mu-Lan Jen
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2024-11-26
- DOI
- https://doi.org/10.58530/2024/0245
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00