mlsanityData to 7 Oct 2026

Multi-view Cross-Modality MR Image Translation for Vestibular Schwannoma and Cochlea Segmentation

arXiv 2303.14998 ↗First posted 27 Mar 2023cs.CV cs.AIcited by 5

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Abstract (arXiv)

In this work, we propose a multi-view image translation framework, which can translate contrast-enhanced T1 (ceT1) MR imaging to high-resolution T2 (hrT2) MR imaging for unsupervised vestibular schwannoma and cochlea segmentation. We adopt two image translation models in parallel that use a pixel-level consistent constraint and a patch-level contrastive constraint, respectively. Thereby, we can augment pseudo-hrT2 images reflecting different perspectives, which eventually lead to a high-performing segmentation model. Our experimental results on the CrossMoDA challenge show that the proposed method achieved enhanced performance on the vestibular schwannoma and cochlea segmentation.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 10 of its 15 references that are in the map. First posted on arXiv 27 Mar 2023.

Builds on

10 of 15 references.

References · 10

  1. 2019Self-training with Noisy Student improves ImageNet classificationcited by 1,304
  2. 2020Contrastive Learning for Unpaired Image-to-Image Translationcited by 637
  3. 2019Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentationcited by 121
  4. 2018SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truthcited by 68
  5. 2020Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translationcited by 60
  6. 2022CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentationcited by 58
  7. 2022QS-Attn: Query-Selected Attention for Contrastive Learning in I2I Translationcited by 39
  8. 2020Scribble-based Domain Adaptation via Co-segmentationcited by 34
  9. 2022COSMOS: Cross-Modality Unsupervised Domain Adaptation for 3D Medical Image Segmentation based on Target-aware Domain Translation and Iterative Self-Trainingcited by 20
  10. 2021Unsupervised Domain Adaptation in Semantic Segmentation Based on Pixel Alignment and Self-Trainingcited by 16

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Cited by year

Citing papers per year: 2023: 4; 2024: 0; 2025: 1.

5 papers.

  1. 2023Learning Site-specific Styles for Multi-institutional Unsupervised Cross-modality Domain Adaptationcited by 3
  2. 2023A 3D Multi-Style Cross-Modality Segmentation Framework for Segmenting Vestibular Schwannoma and Cochleacited by 1
  3. 2023Fine-Grained Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma Segmentationcited by 1
  4. 2025crossMoDA Challenge: Evolution of Cross-Modality Domain Adaptation Techniques for Vestibular Schwannoma and Cochlea Segmentation from 2021 to 2023cited by 1
  5. 2023Image-level supervision and self-training for transformer-based cross-modality tumor segmentationcited by 0