合成偏振敏感光学连贯性断层扫描使用对比的不配对翻译
Thanh Dat Le1, Yong-Jae Lee2, Eunwoo Park3
1Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, 61186, Republic of Korea.
Scientific reports
|December 29, 2024
概括
对比的未配对翻译 (CUT) 从单个OCT图像中生成合成偏振敏感光学连贯断层扫描 (PS-OCT) 图像. 这种高效的方法准确地捕捉了组织双断层,在真实性和组织损伤评估方面表现优于其他模型.
科学领域:
- 生物医学光学 生物医学光学
- 医学成像医学成像
- 组织双重违规性分析
背景情况:
- 对偏振敏感的光学连贯性断层扫描 (PS-OCT) 对于分析生物组织双断裂至关重要.
- 传统上,生成高保真度PS-OCT图像需要广泛的标记数据集.
- 现有的方法很难有效地复制PS-OCT图像中的周期性模式.
研究的目的:
- 开发一种高效的方法,使用对比无对译 (CUT) 来从单个OCT图像中生成合成PS-OCT图像.
- 为了解决数据密集型,像素智能相关联方法在捕获双断形态的局限性.
- 为了评估CUT的性能与PS-OCT图像合成的其他生成模型相比.
主要方法:
- 采用对比的未配对翻译 (CUT),这是一个生成模型,利用未配对数据上的补丁智能的相关性.
- 将CUT与Pix2pix和CycleGAN在6周内内生小鼠肌愈合数据上进行比较.
- 利用ResNet-152模型基于生成的PS-OCT图像进行组织损伤分类.
主要成果:
- CUT成功生成了高保真度合成PS-OCT图像,与原始图像非常接近.
- 与Pix2pix和CycleGAN相比,CUT表现优越 (p < 0.0001),由统计测试证实.
- 使用合成PS-OCT图像,ResNet-152模型在组织损伤评估中达到高达90.13%的准确性.
结论:
- 对比无偶翻译 (CUT) 是一种高效和高效的方法来合成PS-OCT图像.
- CUT准确地捕捉了导致双断裂的基础组织结构特征.
- 拟议的方法为PS-OCT分析提供了显著的图像保真度和效率的改进.
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