From heterogeneous morphogenetic fields to homogeneous regions as a step towards understanding complex tissue dynamics

ABSTRACT Within developing tissues, cell proliferation, cell motility and other cell behaviors vary spatially, and this variability gives a complexity to the morphogenesis. Recently, novel formalisms have been developed to quantify tissue deformation and underlying cellular processes. A major challenge for the study of morphogenesis now is to objectively define tissue sub-regions exhibiting different dynamics. Here, we propose a method to automatically divide a tissue into regions where the local deformation rate is homogeneous. This was achieved by several steps including image segmentation, clustering and region boundary smoothing. We illustrate the use of the pipeline using a large dataset obtained during the metamorphosis of the Drosophila pupal notum. We also adapt it to determine regions in which the time evolution of the local deformation rate is homogeneous. Finally, we generalize its use to find homogeneous regions for cellular processes such as cell division, cell rearrangement, or cell size and shape changes. We also illustrate it on wing blade morphogenesis. This pipeline will contribute substantially to the analysis of complex tissue shaping, and the biochemical and biomechanical regulations driving tissue morphogenesis.

Text Region Extraction From Scene Images Using AGF and MSER

The natural scene images contain text as an integral part of that image that supplies paramount knowledge about it. This information and knowledge can be used in the variety of purposes like image-based searching, automatic number plate recognition, robot navigation, etc. but text region extraction and detection in scenery images could be quite a challenging job due to image blur, distortion, noise, etc. In this paper, we discuss a method for extraction of text regions by generating prospective components by applying maximally stable extremal regions (MSER) and boundary smoothing by Alternating guided image filter, which is one of the newest filters to deal with noise and halo effect elimination. The separation of non-text & text components is achieved by AdaBoost classifier that separates text and non-text on the basis of the three text specific features namely maximum stroke width ratio, compactness, color divergence. The proposed method assist in extracting text regions from the blurred and low contrast natural scene images effectively. The ICDAR 2013 training and testing dataset is applied for the experiments and evaluation of the method. The evaluation is carried out using deteval software for calculating precision, f-measure, recall for the detected, and extracted text regions.

From heterogenous morphogenetic fields to homogeneous regions as a step towards understanding complex tissue dynamics

Within developing tissues, cell proliferation, cell motility, and other cell behaviors vary spatially, and this variability gives a complexity to the morphogenesis. Recently, novel formalisms have been developed to quantify tissue deformation and underlying cellular processes. A major challenge for the study of morphogenesis now is to objectively define tissue sub-regions exhibiting different dynamics. Here we propose a method to automatically divide a tissue into regions where the local deformation rate is homogeneous. This was achieved by several steps including image segmentation, clustering, and region boundary smoothing. We illustrate the use of the pipeline using a large dataset obtained during the metamorphosis of the Drosophila pupal notum. We also adapt it to determine regions where the time evolution of the local deformation rate is homogeneous. Finally, we generalize its use to find homogeneous regions for the cellular processes such as cell division, cell rearrangement, or cell size and shape changes. We also illustrate it on wing blade morphogenesis. This pipeline will contribute substantially to the analysis of complex tissue shaping and the biochemical and bio-mechanical regulations driving tissue morphogenesis.

Computational Synthesis of Large Deformation Compliant Mechanisms Undergoing Self and Mutual Contact

Topologies of large deformation contact-aided compliant mechanisms (CCMs), with self and mutual contact, exemplified via path generation applications, are designed using the continuum synthesis approach. Design domain is parameterized using honeycomb tessellation. Assignment of material to each cell, and generation of rigid contact surfaces, are accomplished via suitably sizing and positioning negative circular masks using the stochastic hill-climber search. To facilitate contact analysis, boundary smoothing is implemented. Mean value coordinates are employed to compute shape functions, as many regular hexagonal cells get degenerated into irregular, concave polygons as a consequence of boundary smoothing. Both geometric and material nonlinearities are considered. The augmented Lagrange multiplier method with a formulated active set strategy is employed to incorporate both self and mutual contact. Synthesized contact-aided compliant continua trace paths with single, and importantly, multiple kinks and experience multiple contact interactions pertaining to both self and mutual contact modes.