Enhancement of MRI images of hamstring avulsion injury using histogram based techniques

A novel histogram based image enhancement technique is introduced to visualize the image more effectively. The proposed method uses hamstring avulsion injury Magnetic Resonance Imaging (MRI) images from the database. First, the image is clipped using the histogram. Second, the image is subdivided into eight sub-images and enhanced individually until a better enhancement rate is maintained to obtain the final output of the proposed method. The proposed method shows effective enhancement for clear visualization of the injury. The strength of the proposed method is compared with different histogram based enhancement techniques based on the parameters such as F-measure, Contrast improvement index (CII), Absolute Mean Brightness Error (AMBE) and Peak Signal to Noise Ratio (PSNR) to determine the efficient enhancement technique. The parameters are defined to be significant
for different enhancement techniques based on the statistical analysis. Further classification
of the enhancement techniques are performed with the help of decision tree classifier. Based on the results of the classifier, the proposed algorithm is stated to be more significant and efficient in enhancing the region of interest in the Hamstring Avulsion Injury MRI images.
Thus the proposed method shows effective enhancement for improved visualization of the hamstring injury for the diagnosis of the state of injury. With these results, the region of injury can be analysed effectively for further processing.