用超声原型指导磁共振卵巢分割，提升小目标边界识别效果。
Cross-Modal MRI Ovary Segmentation in Endometriosis Using Unpaired TVUS Prototype Priors
- 双分支框架融合超声与磁共振特征，利用超声原型对齐解剖结构。
- 在内异症数据集上分割性能提升超5个百分点，显著优于现有方法。
- 适合关注跨模态医学图像分割、尤其是小器官精准定位的研究者。
经阴道超声（TVUS）与磁共振成像（MRI）为子宫内膜异位症影像分析提供互补信息，但现有研究多集中于单模态分析或疾病分类，跨模态卵巢分割仍待探索。针对MRI中卵巢因目标小、边界模糊而难以分割的问题，本文提出一种双分支框架，通过将MedSAM3适配至由TVUS生成的原型库，实现两模态间解剖一致的特征对齐。在相关内异症TVUS与MRI数据集上进行大量实验，结果表明，所提方法在定量与定性上均较多种先进方法提升超过5个百分点。消融实验进一步验证了原型库及源域超声预训练阶段的重要性。
原文摘要 · Abstract (English)
Transvaginal ultrasound (TVUS) and magnetic resonance imaging (MRI) provide complementary information for endometriosis image analysis, yet existing studies mainly focus on single-modality analysis or disease classification, leaving cross-modal ovarian segmentation largely unexplored. In this work, to tackle the increased difficulty of ovary segmentation in MRI due to ovaries' small target size and ambiguous boundaries with surrounding pelvic structures, we propose a dual branch framework for ovary segmentation across TVUS and MRI. More specifically, by adapting MedSAM3 with TVUS-derived prototype bank, we aim to align anatomically consistent feature representations across both modalities. Extensive experiments are conducted on endometriosis-related TVUS and MRI datasets. We observe quantitative and qualitative improvements of over 5 percentage points for the proposed dual-branch approach compared with multiple state-of-the-art methods. Furthermore, our ablation study shows the contribution of individual components such as the prototype bank and the importance of warm-up pretraining in the source TVUS domain.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。