Automated Coregistered Segmentation for Volumetric Analysis of Multiparametric Renal <scp>MRI</scp>
The study establishes a reliable automated pipeline for renal multiparametric MRI postprocessing. The achieved accuracy and efficiency can support improved diagnosis and treatment planning for patients with kidney disease.
Authors
- Lavanya Umapathy (ORCID: https://orcid.org/0000-0002-7224-0930)
- Petros Martirosian (ORCID: https://orcid.org/0000-0001-8383-0883)
- Thomas Küstner
- Cecilia Liang (ORCID: https://orcid.org/0000-0002-6937-1681)
- Ferdinand Seith (ORCID: https://orcid.org/0000-0002-9696-2954)
- Aya Ghoul (ORCID: https://orcid.org/0009-0002-1221-1756)
- Isabelle Loster
- Bernd Kuhn
- Sergios Gatidis
Institutions
- STZ eyetrial (DE)
- Siemens Healthineers (Germany) (DE)
- New York University (US)
- University of Tübingen (DE)
- Stanford University (US)
Publication Details
- Journal
- Magnetic Resonance in Medicine
- Published
- 2026-02-04
- DOI
- https://doi.org/10.1002/mrm.70288
- Primary Topic
- Renal cell carcinoma treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00