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Lung injury caused by influenza virus infection is widespread. Understanding lung damage and repair progression post infection requires quantitative spatiotemporal information on various cell types mapping into the tissue structure. Based on high content images acquired from an automatic slide scanner, we have developed algorithms to quantify cell infiltration in the lung, loss and recovery of Clara cells in the damaged bronchioles and alveolar type II cells (AT2s) in the damaged alveolar areas, and induction of pro-surfactant protein C (pro-SPC)-expressing bronchiolar epithelial cells (SBECs). These quantitative analyses reveal: prolonged immune cell infiltration into the lung that persisted long after the influenza virus was cleared and paralleled with Clara cell recovery; more rapid loss and recovery of Clara cells as compared to AT2s; and two stages of SBECs from Scgb1a1+ to Scgb1a1-. These results provide evidence supporting a new mechanism of alveolar repair where Clara cells give rise to AT2s through the SBEC intermediates and shed light on the understanding of the lung damage and repair process. The approach and algorithms in quantifying cell-level changes in the tissue context (cell-based tissue informatics) to gain mechanistic insights into the damage and repair process can be expanded and adapted in studying other disease models. [ABSTRACT FROM AUTHOR]

We propose a transmissive metalens utilizing graphene for highly efficient dynamic focusing at terahertz frequencies. The subwavelength metaatom of the metalens consists of a metallic grating layer, dielectric spacer and a graphene patch. Rigorous design of the space-dependent graphene patches allows the desired phase discontinuity for focusing the orthogonal linear polarization component relative to the excitation. Furthermore, due to the different sensitivities of the constitutive metaatoms to the variation of graphene chemical potential, the focusing dynamics are designable. By simply changing the arrangement of the metaatoms in a metalens, the focal length can be designed to vary in a large dynamic range or to remain still as the chemical potential changes from 0.5 eV to 0.8 eV. Therefore, the metalens can either be used for dynamic or stable imaging regardless of the fluctuations of graphene conductivity, which allows the metalens to meet the needs of different application systems. [ABSTRACT FROM AUTHOR]

In this paper, an automated method of boundary detection of the left ventricle (LV) is proposed. The method uses a watershed transform and morphological operation to locate the region containing the LV, then performs snake deformation with a multiscale directional edge map for the detection of the endocardial boundary of the LV. [ABSTRACT FROM AUTHOR]

This paper concerns multiphase piecewise smooth image segmentation with intensity inhomogeneities. Traditional methods based on the Mumford-Shah (MS) model require solving complicated diffusion equations evolving in irregular subdomains, leading to significant difficulties in efficient and accurate segmentation, especially in multiphase scenarios. In this paper, we propose a general framework to modify the MS model by using smoothing operators that can avoid the complicated implementation and inaccurate segmentation of traditional approaches. A detailed analysis connecting the smoothing operators and the diffusion equations is given to justify the modification. In addition, we present an efficient algorithm based on the direct augmented Lagrangian method, which requires fewer parameters than the commonly used augmented Lagrangian method. Typically, the smoothing operator in the general model is chosen to be Gaussian kernel, the bilateral kernel, and the directional diffusion kernel, respectively. Ample numerical results are provided to demonstrate the efficiency and accuracy of the modified model and the proposed minimization algorithm through various comparisons with existing approaches.