将视网膜基础模型范式从切片转变为光学连贯性断层扫描的体积
Raphael Judkiewicz1, Eran Berkowitz2,3,4, Meishar Meisel2
1Faculty of Biomedical Engineering, Technion-IIT, Haifa, Israel.
NPJ digital medicine
|March 5, 2026
概括
像V-JEPA这样的视频基础模型显示出在光学连贯断层扫描 (OCT) 中分析3D视网膜结构的前景. 与传统方法相比,这种方法显著改善了眼睛疾病的检测.
科学领域:
- 眼科医生 眼科 眼科
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 光学连贯断层扫描 (OCT) 在眼科中对视网膜成像至关重要.
- 目前用于OCT分析的基础模型通常使用单个B扫描,忽视了有价值的体积数据.
- 预训练的模型可以加速开发,但需要适应3D环境.
研究的目的:
- 调查视频基础模型在分析 OCT 体积数据方面的有效性.
- 将视频模型的诊断性能与眼科中基于图像的模型进行比较.
- 评估基于变压器的视频模型对3D医学成像的潜力.
主要方法:
- 将V-JEPA视频基础模型与已建立的模型 (RETFound,VisionFM,DINOv2) 进行比较.
- 在五个OCT数据集上进行微调模型,用于检测与年龄相关的黄斑退化和眼视神经病变.
- 使用接收器操作特征曲线 (AUROC) 下面的面积来评估性能.
主要成果:
- 与所有基于图像的基础模型相比,V-JEPA表现出优越或相等的性能.
- V-JEPA的平均AUROC为0.94,超过了最佳图像模型的0.90 (p < 0.001).
- 这项研究是首次将基于变压器的视频模型应用于 OCT 的体积数据.
结论:
- 视频基础模型有效地从OCT扫描中捕获3D视网膜结构.
- 与传统的基于图像的模型相比,V-JEPA为眼科疾病提供了改进的诊断能力.
- 基于变压器的视频模型对推进3D医学成像分析具有重大前景.
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