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Detection of Leukocytes in Intravital Video Microscopy Based on the Analysis of Hessian Matrix Eigenvalues

机译:基于Hessian矩阵特征值分析的活体视频显微镜中白细胞检测

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Detection of rolling and adhered leukocytes in intravital microscopy image sequences is an important task in studies of leukocyte-endothelial interactions in the microcirculation of living small animals under different inflammatory conditions. This procedure is usually performed by visual assessment of the image sequences. However, despite being tedious and time consuming, this procedure is prone to the inter- and intra-observer variability. In this work, we developed an automated computer system for the detection of leukocytes in intravital video microscopy. First, the video frames were processed by the bilateral filter to reduce noise while preserving sharp edges. Then, a demons-based image registration technique was applied to minimize animal motion. Finally, the detection of leukocytes was performed by local analysis of Hessian matrix Eigen values. Quantitative and qualitative evaluation of the proposed method were conducted by using 220 video frames obtained from an experimental study performed on the brain microvasculature of mice. The proposed method was compared with the template matching technique using precision, recall and F1-Score measures. For the Hessian-based method, the results of precision, recall and F1-Score were, respectively, equal to 0.81, 0.86, and 0.83. For direct comparison, the results obtained for the template matching technique were 0.86, 0.73 and 0.79.
机译:在活体小动物在不同炎症条件下微循环中白细胞-内皮相互作用的研究中,在活体内显微镜图像序列中检测滚动和粘附的白细胞是一项重要的任务。通常通过视觉评估图像序列来执行此过程。然而,尽管繁琐且费时,但是该过程易于观察者之间和观察者内部的可变性。在这项工作中,我们开发了一种自动计算机系统,用于在活体视频显微镜中检测白细胞。首先,通过双边滤波器对视频帧进行处理,以在保持锐利边缘的同时减少噪声。然后,基于恶魔的图像配准技术被应用于使动物运动最小化。最后,通过对Hessian矩阵特征值进行局部分析来检测白细胞。通过使用220个视频帧对提议的方法进行定量和定性评估,该视频帧是通过对小鼠的大脑微脉管系统进行的实验研究获得的。将该方法与使用精度,召回率和F1-Score度量的模板匹配技术进行了比较。对于基于Hessian的方法,精度,召回率和F1-Score的结果分别等于0.81、0.86和0.83。为了直接比较,通过模板匹配技术获得的结果为0.86、0.73和0.79。

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