发表机构
Yonsei University（延世大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对高频超声皮肤层分割标注稀缺问题，提出物理引导合成HFUS生成框架，通过k-Wave模拟生成配对数据用于预训练，在真实数据上微调后性能与真实训练相当，多数架构Dice/IoU提升。
AI 中文摘要
高频超声（HFUS）能够无创地可视化浅表皮肤结构，但自动皮肤层分析受到密集标注数据稀缺的限制。现有的真实HFUS数据集通常提供表皮和表皮下低回声带（SLEB）等浅表目标的标注，而深层结构如真皮、皮下组织、筋膜和肌肉的密集标签很少可用。我们提出了一种物理引导的合成HFUS生成框架，用于皮肤层分割。该框架构建多层声学皮肤模型，分配依赖于层的声学特性，并使用k-Wave模拟生成配对的合成HFUS图像、密集层掩模和模拟元数据。为了评估生成的数据是否提供可迁移的监督，我们将其用于下游分割预训练，并在真实Mendeley HFUS数据上微调模型。合成预训练后接真实微调，在真实域上的性能与仅使用真实数据训练相当，并在四种评估的可训练架构中的三种上提高了平均Dice/IoU。这些结果表明，物理引导的合成HFUS图像包含可迁移的解剖和纹理线索，用于真实域皮肤层分割，尽管需要进一步缩小合成与真实外观差距以实现更大的收益。代码和数据可在以下网址获取：此https URL。
英文摘要
High-frequency ultrasound (HFUS) enables noninvasive visualization of superficial skin structures, but automated skin-layer analysis is limited by the scarcity of densely annotated data. Existing real HFUS datasets commonly provide annotations for superficial targets such as the epidermis and subepidermal low-echogenic band (SLEB), while dense labels for deeper structures such as dermis, subcutaneous tissue, fascia, and muscle are rarely available. We propose a physics-guided synthetic HFUS generation framework for skin layer segmentation. The framework constructs multilayer acoustic skin phantoms, assigns layer dependent acoustic properties, and uses k-Wave simulation to generate paired synthetic HFUS images, dense layer masks, and simulation metadata. To evaluate whether the generated data provide transferable supervision, we use it for downstream segmentation pretraining and fine-tune the models on real Mendeley HFUS data. Synthetic pretraining followed by real fine-tuning achieved real-domain performance comparable to real-only training and improved mean Dice/IoU in three of four evaluated trainable architectures. These results suggest that physics-guided synthetic HFUS images contain transferable anatomical and textural cues for real-domain skin layer segmentation, although further reduction of the synthetic-real appearance gap is needed to enable greater gains. The code and data are available at: https://github.com/Finn-02/synthetic-hfus-skin-layer-segmentation.
Comments12 pages, accepted at MICCAI DH4H Workshop 2026
