meshography workshop

<p>Leveraging the meshing of frog gastrocnemius muscle from digital photography using artificial neural networks.</p> <p>This data collection supports the finding in our paper submitted to the INTERNATIONAL JOURNAL OF NUMERICAL METHODS IN BIOMEDICAL ENGINEERING&quot;, on Oct.20,2018.</p> <p>There are two folders (left and right) containing 15 images each, processed for edge detection of the left and right object contours.</p> <p>There are also some Matlab scripts and functions, for data preparation and training of a Bayesian backpropagation neural network.</p> <p>The script (kod2.m) is associated with the polynomial fitting procedure to the contours, and it utilized the function (fiterror.m) in the process.</p> <p>The file (polinomtablo4th.mat) contains the output of the fitting procedure, and is used by the neural networking script (plotneur4th.m).</p> <p>Finally, the unit cylinder mesh are processed through the network, to produce the 1767 node, 1440 hexahedral-type element FEAP mesh (wIplant2), of the muscle shown in (mesh_view2.png).</p> <p>The codes are based in the MATLAB R15b, image processing and neural network toolboxes.</p>