Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
602-02-006 ISMRM Abstract

Deep Learning-based Automatic Oblique Scan Angulation for Axial Prostate MRI

Primary: Body - Prostate
Secondary: Acquisition & Reconstruction - AI methods
602-02-006 · Prostate MRI: Methodological Developments · Thursday, 14 May, 1:40 PM–3:30 PM · Hall 1B
Keywords: Prostate MRI MRI Workflow optimization
Accepted
Robert Grimm 1, Robin Hoepp1, Tristan Rauhut1, Cornelius Jacob1, Guillaume Chabin2, Heinrich von Busch3, Florian Knoll4, Sohrab A Mirak5, Leonardo K BIttencourt5
1Research & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany
2Technology Excellence, Digital Technology and Innovation, Siemens Healthcare SAS, Paris, France
3Digital & Automation, Siemens Healthineers AG, Forchheim, Germany
4Department Artificial Intelligence in Biomedical Engineering (AIBE), Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
5Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, United States of America
Presenting Author: Robert Grimm

Synopsis

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References

1. Cornford P, van den Bergh RCN, Briers E et al. EAU-EANM-ESTRO-ESUR-ISUP-SIOG Guidelines on Prostate Cancer-2024 Update. Part I: Screening, Diagnosis, and Local Treatment with Curative Intent. Eur Urol 86: 148 (2024). https://doi.org/10.1016/j.eururo.2024.03.027 [doi]
2. Franiel T, Asbach P, Beyersdorff D et al: Updated Recommendations of the DRG and BDR on Patient Preparation and Scanning Protocol. Rofo 193(7), 763-777 (2021). https://doi.org/10.1055/a-1406-8477 [doi]
3. Isensee F, Jaeger PF, Kohl SAA et al. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods 18, 203–211 (2021). https://doi.org/10.1038/s41592-020-01008-z [doi]
4. Litjens, G, Debats, O, Barentsz, J, Karssemeijer, N, & Huisman, H. SPIE-AAPM PROSTATEx Challenge Data (Version 2) [Data set]. The Cancer Imaging Archive (2017). https://doi.org/10.7937/K9TCIA.2017.MURS5CL [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/602-02-006