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February 26, 2024Medical PhysicsOpen Access

Deep‐learning‐based joint rigid and deformable contour propagation for magnetic resonance imaging‐guided prostate radiotherapy

Iris D. Kolenbrander Matteo Maspero Allard A. Hendriksen Ryan Pollitt Jochem R.N. van der Voort van Zyp Cornelis A. T. van den Berg Josien P. W. Pluim Maureen A. J. M. van Eijnatten

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Abstract

Deep learning-based unsupervised image registration has recently been proposed, promising fast registration. However, it has yet to be adopted in the online adaptive magnetic resonance imaging-guided radiotherapy (MRgRT) workflow.

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Cite This Study

Kolenbrander et al. (2024) studied this question.

synapsesocial.com/papers/68e777b3b6db6435876ecf74 https://doi.org/10.1002/mp.17000

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Weakly supervised deep learning for multimodal MRI-TRUS registration: Toward assisting prostate biopsy guidance2025 · 1 citations
2Deformable registration of magnetic resonance images using unsupervised deep learning in neuro-/radiation oncology2024 · 3 citations
3Segmentation regularized training for multi-domain deep learning registration applied to magnetic resonance-guided prostate cancer radiotherapyOriginal Research · 2026
4Attention-Guided TransMorph for Real-Time Tumor Tracking in Cine-MRIOriginal Research · 2026
5Deep learning-based deformable image registration with bilateral pyramid to align pre-operative and follow-up magnetic resonance imaging (MRI) scans2024 · 4 citations

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