Computed tomography image enhancement using the concept of fuzzy logic.
Diagnostic features in computed tomography (CT) images vary widely due to the vague nature (fuzziness) of functional characteristics in organ pathologies. Classical image enhancement techniques cannot adapt to the characteristics of this nature. A method based on fuzzy logic is given in this paper. In this method the image of interest is transformed into a fuzzy plane using fuzzifiers which can be changed to select a crossover point. A contrast intensification operator (INT) is then applied. The operator increases the grade of membership of those values which lie above the crossover point and decreases the same for those pixels which lie below it, thereby increasing the contrast and reducing the fuzziness. Quantitative measures of fuzziness which reflect a sort of quantitative measure of image quality have also been studied. Using digitized CT images it has been shown that at early stages of a disease, when the contrast of the pathological tissues is very low, the visibility of the disease could be considerably improved using this technique.
Mir
A H
AH
Centre for Biomedical Engineering, IIT Delhi, Hauz Khas, India.
Hanmandlu
M
M
Tandon
S N
SN
D017143:Fuzzy Logic; D006801:Humans; D008099:Liver / Q000000981:diagnostic imaging*; D008113:Liver Neoplasms / Q000000981:diagnostic imaging*; D011856:Radiographic Image Enhancement; D014057:Tomography, X-Ray Computed