伪染用于分辨率和拓不变的皮层分片
Pablo Blasco Fernandez1,2, Karthik Gopinath2, John Williams-Ramirez2
1ETH Zurich, Zurich, Switzerland.
概括
我们推出一种新的伪染逆染 (PRIR) 方法来进行大脑皮层分片. PRIR克服了网格拓的局限性,并准确地分割了表面扫描,实现了最先进的结果.
科学领域:
- 神经成像
- 计算神经科学
- 医学图像分析
背景情况:
- 在神经成像分析中, 皮层网格分片至关重要.
- 现有的方法通常需要球状网状拓,不包括不完整或噪音数据.
- 深度学习与非描述性的表面扫描和远程依赖性相斗争.
研究的目的:
- 开发一种针对拓缺陷和表面扫描噪声的新型皮质网格分片方法.
- 用基于染的框架将网格分片重新定义为2D细分任务.
- 提高对各种神经成像数据的大脑分片的准确性和适用性.
主要方法:
- 建议使用直接反向染框架进行"伪染反向染" (PRIR).
- 从多个视图中染网格,将正常向量投射到三通道图像中.
- 使用U-Nets进行二维图像细分,并将结果映射到三维顶点.
- 使用马科夫随机场进行后处理,以确保流性和处理阻塞.
主要成果:
- 与传统和深度学习方法不同,PRIR独立于网格拓.
- 在拓正确的白质网上实现最先进的精度.
- 显示模拟和真实表面扫描的准确细分,包括噪音数据.
结论:
- PRIR提供了一个强大的多功能解决方案,用于皮质网格分片.
- 该方法有效处理拓缺陷,并捕获远程依赖.
- 通过精确细分具有挑战性的数据集,PRIR促进了神经影像分析.
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