Extraction of Individual Filaments from 2D Confocal Microscopy Images of Flat Cells

Modeling and Identification of Amnioserosa Cell Mechanical Behavior by Using Mass-Spring Lattices

Various mechanical models of live amnioserosa cells during Drosophila melanogaster's dorsal closure are proposed. Such models account for specific biomechanical oscillating behaviors and depend on a different set of parameters. The identification of the parameters for each of the proposed models is accomplished according to a least-squares approach in such a way to best fit the cellular dynamics extracted from live images. For the purpose of comparison, the resulting models after identification are validated to allow for the selection of the most appropriate description of such a cell dynamics. The proposed methodology is general and it may be applied to other planar biological processes.

Three-Dimensional Segmentation of the Ex-Vivo Anterior Lamina Cribrosa From Second-Harmonic Imaging Microscopy

The lamina cribrosa (LC) is a connective tissue in the posterior eye with a complex mesh-like trabecular microstructure, through which all the retinal ganglion cell axons and central retinal vessels pass. Recent studies have demonstrated that changes in the structure of the LC correlate with glaucomatous damage. Thus, accurate segmentation and reconstruction of the LC is of utmost importance. This paper presents a new automated method for segmenting the microstructure of the anterior LC in the images obtained via multiphoton microscopy using a combination of ideas. In order to reduce noise, we first smooth the input image using a 4-D collaborative filtering scheme. Next, we enhance the beam-like trabecular microstructure of the LC using wavelet multiresolution analysis. The enhanced LC microstructure is then automatically extracted using a combination of histogram thresholding and graph-cut binarization. Finally, we use morphological area opening as a postprocessing step to remove the small and unconnected 3-D regions in the binarized images. The performance of the proposed method is evaluated using mutual overlap accuracy, Tanimoto index, F-score, and Rand index. Quantitative and qualitative results show that the proposed algorithm provides improved segmentation accuracy and computational efficiency compared to the other recent algorithms.

Super-resolution imaging for monitoring cytoskeleton dynamics

The cytoskeleton is a key cellular structure that is important in the control of cellular movement, structure, and sensing. To successfully image the individual cytoskeleton components, high resolution and super-resolution fluorescence imaging methods are needed. This review covers the three basic cytoskeletal elements and the relative benefits and drawbacks of fixed versus live cell imaging before moving on to recent studies using high resolution and super-resolution techniques. The techniques covered include the near-diffraction limited imaging methods of confocal microscopy and TIRF microscopy and the super-resolution fluorescence imaging methods of STORM, PALM, and STED.