Sparse Principal Component Analysis aims to simplify complex data by finding important patterns. Traditional methods make it hard to understand the results, so a new method was developed to make the patterns easier to see. This new method keeps the important parts of the data while reducing its size. Tests show that this method can help pick out important features in images and improve the analysis of brain scans.