图像重建方法中的线性验证 斑点对比光学断层扫描
Alexander C Howard1, Byungchan Kim1, Laura Carlton1
1The authors are with the Department of Biomedical Engineering, Neurophotonics Center, Boston University, Boston, MA 02215 USA.
IEEE journal of selected topics in quantum electronics : a publication of the IEEE Lasers and Electro-optics Society
|August 22, 2025
概括
现在可以更准确地绘制大脑血液流动图. 瑞托夫近似为改进的图像重建提供了可靠的前向模型,在显著的血流变化方面优于第一个博恩近似.
科学领域:
- 生物医学光学
- 神经成像
- 光学光谱学
背景情况:
- 斑点对比光谱学 (SCOS) 不侵入性地测量大脑血液流动和大脑功能.
- 斑点对比光学断层扫描 (SCOT) 扩展了SCOS用于血液流动变异映射.
- 在SCOT图像重建中的线性假设可能并不总是正确的.
研究的目的:
- 开发和验证使用Rytov近似的SCOT前模型.
- 将Rytov近似与第一个Born近似和蒙特卡洛模拟进行比较.
- 为了证明Rytov近似对人类大脑活动的准确SCOT图像重建的实用性.
主要方法:
- 使用Rytov近似来解决相关扩散方程构建了一个SCOT前模型.
- 将Rytov近似结果与第一个Born近似和蒙特卡洛模拟进行比较.
- 开发了血液流量指数 (BFi),并使用了灵敏度矩阵方法来解决线性前向和反向问题.
主要成果:
- 里托夫近似结果与蒙特卡洛模拟结果非常相符.
- 对于超过30%的血流变化,第一生儿的近似值显示出显著的偏差.
- 使用高密度SCOS成功重建人类大脑的图像.
结论:
- 当血流变化超过30%时,建议使用Rytov近似比SCOT的第一个Born近似.
- 开发的BFi与局部脑血流变化有线相关,使线性重建方法成为可能.
- 经过验证的基于Rytov的前模型指导SCOT系统设计和数据分析,以增强神经成像.
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