Bone Age Classification Using CNN Algorithm

The MATLAB Graphical User Interface (GUI) facilitates bone age assessment through hand X-ray and MRI images, streamlining the process for medical practitioners and researchers. Users can load X-ray and MRI images, visualize the original and processed images, and employ a pre-trained neural network for the automatic classification of bone agestages. The tool integrates a 4-level discrete wavelet transform to extract essential features reflecting bone maturity, utilizing Haralick features like energy, contrast, correlation, homogeneity, and entropy. Furthermore, the GUI offers animage segmentation option, emphasizing specific bone-related regions for detailed analysis. Performance metrics such as sensitivity, specificity, and accuracy can be evaluated with a validation button, providing a quantitative measure of the classification's reliability. Overall, this GUI serves as a comprehensive solution for bone age analysis, combining image loading, classification, wavelet transform, feature extraction, segmentation, and performance assessment within an intuitive interface. It caters to the needs of medical professionals, offering a user-friendly platform to enhance the efficiency and accuracy of bone age assessments