Selective contrast enhancement of space occupying lesions in brain using vague set approach

In present work generalized notion of fuzzy sets is applied to achieve more flexible and intelligent contrast enhancement system for medical images of section of human bain. Applying wavelet transform two images are obtained, one is containing low frequency components (LF) other one is containing high frequency components (HF). LF image is fuzzified by fuzzy c-means clustering (FCM) technique with justified number of clusters to enhance the approximate structure. The HF images, which are highlighting narrow protrusions and other fine details are fuzzified with justified number of clusters also. Vague set approach containing interval based membership function captures the uncertainties between truly affected tumor region and normal tissues. After highlighting the tumors properly, both LF and HF images are transformed back to the original resolution by inverse wavelet transform. The results show that the proposed method can enhance the images more successfully and provide better contrast for visual interpretation.