Syntactic approach to reconstruct simple and complex medical images

Most researchers find pattern recognition to be an interesting area to study. Objects that are different in shape, size, colour, and scale are easy to identify apart. Most of the available models for object recognition use a statistical approach, which works well if there is no noise in the image and the image is simple. However, this method fails if the pattern is more complicated, and there may be ambiguous results for complex pattern datasets. In that case, it would be better to use structural pattern recognition. We focused on the syntactic approach to describing the features as knowledge, which could make a big difference in theoretical computer science. Experiments have been performed on Brain MRI datasets and own dataset. To identify the performance of the reconstruction algorithm MAE, CPU time, and RMSE and iteration of the frame are calculated.