Multi-plane vision transformer for hemorrhage classification using axial and sagittal MRI data

Das BK, Zhao G, Mailhe B, Re TJ, Comaniciu D, Gibson E, Maier A (2026)

Publication Type: Journal article

Publication year: 2026

Journal

Scientific Reports Nature Publishing Group: Open Access Journals - Option B

Book Volume: 16

Article Number: 9333

Journal Issue: 1

DOI: 10.1038/s41598-026-44524-2

Abstract

Identifying brain hemorrhages from magnetic resonance imaging (MRI) is a critical task for healthcare professionals. The diverse nature of MRI acquisitions with varying contrasts and orientation introduces complexity in identifying hemorrhage using neural networks. For acquisitions with varying orientations, traditional methods often involve resampling images to a fixed plane, which can lead to information loss. To address this, we propose a 3D multi-plane vision transformer (MP-ViT) for hemorrhage classification with varying orientation data. It employs two separate transformer encoders for axial and sagittal contrasts, using cross-attention to integrate information across orientations. MP-ViT also includes a modality indication vector to provide missing contrast information to the model. The effectiveness of the proposed model is demonstrated with extensive experiments on a real-world clinical dataset consisting of 10,084 training, 1,289 validation, and 1,496 test subjects. MP-ViT achieved substantial improvement in area under the curve (AUC), outperforming the vision transformer (ViT) by 5.5% and CNN-based architectures by 1.8%. These results highlight the potential of MP-ViT in improving performance for hemorrhage detection when different orientation contrasts are needed.

Authors with CRIS profile

Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

Involved external institutions

Siemens Healthineers (Germany) DE Germany (DE)

How to cite

APA:

Das, B.K., Zhao, G., Mailhe, B., Re, T.J., Comaniciu, D., Gibson, E., & Maier, A. (2026). Multi-plane vision transformer for hemorrhage classification using axial and sagittal MRI data. Scientific Reports, 16(1). https://doi.org/10.1038/s41598-026-44524-2

MLA:

Das, Badhan Kumar, et al. "Multi-plane vision transformer for hemorrhage classification using axial and sagittal MRI data." Scientific Reports 16.1 (2026).

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