mlsanityData to 14 Oct 2026

Coarse-to-Fine Joint Registration of MR and Ultrasound Images via Imaging Style Transfer

arXiv 2508.05240 ↗First posted 7 Aug 2025eess.IV cs.AI cs.CVcited by 1

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Abstract (arXiv)

We developed a pipeline for registering pre-surgery Magnetic Resonance (MR) images and post-resection Ultrasound (US) images. Our approach leverages unpaired style transfer using 3D CycleGAN to generate synthetic T1 images, thereby enhancing registration performance. Additionally, our registration process employs both affine and local deformable transformations for a coarse-to-fine registration. The results demonstrate that our approach improves the consistency between MR and US image pairs in most cases.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 4 of its 18 references that are in the map. First posted on arXiv 7 Aug 2025.

Builds on

4 of 18 references.

References · 4

  1. 2018VoxelMorph: A Learning Framework for Deformable Medical Image Registrationcited by 662
  2. 2020SynthMorph: learning contrast-invariant registration without acquired imagescited by 140
  3. 2018Unpaired Brain MR-to-CT Synthesis using a Structure-Constrained CycleGANcited by 31
  4. 2023Anatomy-aware and acquisition-agnostic joint registration with SynthMorphcited by 19

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026A Systematic Benchmark of Intraoperative Ultrasound-to-MR Synthesis for Brain Tumour Surgerycited by 2