Biomimetics
Mohammad Reza Nikmaneshi; Bahar Firoozabadi; Mohammad Saeid Saeidi
Volume 7, Issue 2 , June 2013, , Pages 97-105
Abstract
The front part of a cell is divided to two regions called lamellum and lamellipodium (lamellipodial). Internal flows in this part plays an essential role for cell migration. Indeed, there are many protein filaments called actin in lamellum and lamellipodium, which induce the cell motion with polymerization ...
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The front part of a cell is divided to two regions called lamellum and lamellipodium (lamellipodial). Internal flows in this part plays an essential role for cell migration. Indeed, there are many protein filaments called actin in lamellum and lamellipodium, which induce the cell motion with polymerization in the leading edge of the cell. The actin filaments adhere to the extracellular matrix (ECM) by means of focal adhesions and they have contact by myosin motor proteins. The myosin motor proteins cause actin retrograde and anterograde flow exerted contractile stress on them. The focal adhesions exert frictional stress on the actin filaments. In this work, we developed a two-dimensional continuum model of the fanshaped lamellipodial to obtain the actin retrograde flow. In addition, the actin filaments are assumed as a highly viscous Newtonian fluid. We also investigated the effects of the myosin distribution and cell speed on the actin flow. Our results include actin flow and myosin distribution in the moving cell, and we also illustrate their relation together. These results accord to reported experimentally and numerically data, and are verified with them.
Cell Biomechanics / Cell Mechanics / Mechanobiology
Naser Mehrshad; Mohammad Hasan Ghasemian Yazdi
Volume 1, Issue 2 , June 2007, , Pages 119-129
Abstract
Simple cells in primary visual cortex respond to the local, oriented edge segments within their receptive fields. In this study, we present a new edge detection method based on the computational model of these cells. Firstly, the response of a set of simple cells for a number of different preferred orientations ...
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Simple cells in primary visual cortex respond to the local, oriented edge segments within their receptive fields. In this study, we present a new edge detection method based on the computational model of these cells. Firstly, the response of a set of simple cells for a number of different preferred orientations are calculated. Then, the intensity gradient for each pixel is obtained using the linear summation of these responses. Some parameters of simple cell computational model are calculated in such a way that a set of goals (good detection, good localization and only one response to a single edge) achieving for the resulting operator. Considering the properties of medical images, the proposed operator is useful for medical image edge detection. The synthesis and medical images with their associated ground truth edge maps are used to assess performance of the proposed method. The results obtained from the proposed method are found to be better and more stable with respect to the input parameters than those from many well known edge detectors (e.g. Canny edge detector).
