Ringuette Dene, Nauenberg Jacob, Monnier Philippe P, Carlen Peter L, Levi Ofer
The Institute of Biomaterials and Biomedical Engineering, University of Toronto, 164 College Street, Toronto, Ontario, M5S 3G9, Canada.
Division of Fundamental Neurobiology, Toronto Western Research Institute, 60 Leonard Ave, Toronto, Ontario M5T 2S8, Canada.
Biomed Opt Express. 2018 Oct 19;9(11):5615-5634. doi: 10.1364/BOE.9.005615. eCollection 2018 Nov 1.
Single-frame blood flow maps from laser speckle contrast imaging (LSCI) contain high spatiotemporal variation that obscures high spatial-frequency vascular features, making precise image registration for signal amplification challenging. In this work, novel bivariate standardized moment filters (BSMFs) were used to provide stable measures of vessel edge location, permitting more robust LSCI registration. Relatedly, BSMFs enabled the stable reconstruction of vessel edges from sparsely distributed blood flow map outliers, which were found to retain most of the temporal dynamics. Consequently, data discarding and BSMF-based reconstruction enable efficient real-time quantitative LSCI data compression. Smaller LSCI-kernels produced log-normal blood flow distributions, enhancing sparse-to-dense inference.
激光散斑对比成像(LSCI)的单帧血流图包含高时空变化,这会掩盖高空间频率的血管特征,使得用于信号放大的精确图像配准具有挑战性。在这项工作中,新型双变量标准化矩滤波器(BSMF)被用于提供血管边缘位置的稳定测量,从而实现更稳健的LSCI配准。相关地,BSMF能够从稀疏分布的血流图异常值中稳定重建血管边缘,发现这些异常值保留了大部分时间动态信息。因此,数据丢弃和基于BSMF的重建能够实现高效的实时定量LSCI数据压缩。较小的LSCI内核产生对数正态血流分布,增强了从稀疏到密集的推理。