生物形状和图像的生成建模使用概率形状采样器
Emily T Winn-Nuñez1, Hadley Witt2,3, Dhananjay Bhaskar4
1Division of Applied Mathematics, Brown University, Providence, RI, USA.
bioRxiv : the preprint server for biology
|January 23, 2024
概括
我们介绍了A形采样器,这是一个新的概率框架,用于生成现实的二维和三维形状. 这个工具有助于理解计算生物学中的形态变异,特别是当真实数据稀缺时.
科学领域:
- 计算生物学是一种计算生物学.
- 生物统计学 生物统计学
- 几何形态仪表的几何形态仪表.
背景情况:
- 了解形态变异在计算生物学中至关重要.
- 目前用于形状分析的方法经常与有限或无法访问的真实世界数据作斗争.
- 现有的形状生成模型缺乏系统评估能力.
研究的目的:
- 介绍一个新的概率框架,A形采样器,用于生成现实的2D和3D形状.
- 为从真实数据中学习形状分布提供一种方法.
- 为了方便对形状变化的子图像模型的评估.
主要方法:
- 开发了一个基于可学习的概率分布生成形状的概率框架.
- 利用框架生成2D和3D形状.
- 用概念验证示例和生物应用来展示框架.
主要成果:
- 使用A形样本仪成功生成了现实的2D和3D形状.
- 应用该框架生成中性粒细胞图像和灵长类动物牙的3DCT扫描.
- 提供A形采样器R包作为开源软件.
结论:
- A型采样器提供了一种灵活而强大的方法来建模形态变异.
- 该框架解决了数据可用性和形状分析中的生成模型评估的局限性.
- 开源可用性促进了计算生物学更广泛的采用和进一步发展.
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