College of Electronics and Information Engineering, Hebei University, Baoding 071002, China.
School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China.
J Healthc Eng. 2017;2017:1848314. doi: 10.1155/2017/1848314. Epub 2017 Jul 30.
Analysis of cell mobility is a key issue for abnormality identification and classification in cell biology research. However, since cell deformation induced by various biological processes is random and cell protrusion is irregular, it is difficult to measure cell morphology and motility in microscopic images. To address this dilemma, we propose an improved variation optical flow model for quantitative analysis of intracellular motility, which not only extracts intracellular motion fields effectively but also deals with optical flow computation problem at the border by taking advantages of the formulation based on and norm, respectively. In the energy functional of our proposed optical flow model, the data term is in the form of norm; the smoothness of the data changes with regional features through an adaptive parameter, using norm near the edge of the cell and norm away from the edge. We further extract histograms of oriented optical flow (HOOF) after optical flow field of intracellular motion is computed. Then distances of different HOOFs are calculated as the intracellular motion features to grade the intracellular motion. Experimental results show that the features extracted from HOOFs provide new insights into the relationship between the cell motility and the special pathological conditions.
细胞迁移分析是细胞生物学研究中异常识别和分类的关键问题。然而，由于各种生物过程引起的细胞变形是随机的，并且细胞突起是不规则的，因此很难在显微镜图像中测量细胞形态和运动。为了解决这个难题，我们提出了一种改进的变分光流模型，用于定量分析细胞内运动，该模型不仅可以有效地提取细胞内运动场，还可以利用基于 和 范数的公式分别在边界处处理光流计算问题。在我们提出的光流模型的能量泛函中，数据项的形式为 范数；数据的平滑度通过自适应参数随区域特征而变化，在细胞边缘附近使用 范数，在远离边缘的地方使用 范数。我们进一步在计算出细胞内运动的光流场之后提取定向光流（HOOF）的直方图。然后计算不同 HOOF 的距离作为细胞内运动的特征来对细胞内运动进行分级。实验结果表明，从 HOOF 中提取的特征为细胞运动与特殊病理条件之间的关系提供了新的见解。
