Enhancing digital cephalic radiography with mixture models and local gamma correction.
We present a new algorithm, called the soft-tissue filter, that can make both soft and bone tissue clearly visible in digital cephalic radiographies under a wide range of exposures. It uses a mixture model made up of two Gaussian distributions and one inverted lognormal distribution to analyze the image histogram. The image is clustered in three parts: background, soft tissue, and bone using this model. Improvement in the visibility of both structures is achieved through a local transformation based on gamma correction, stretching, and saturation, which is applied using different parameters for bone and soft-tissue pixels. A processing time of 1 s for 5 Mpixel images allows the filter to operate in real time. Although the default value of the filter parameters is adequate for most images, real-time operation allows adjustment to recover under- and overexposed images or to obtain the best quality subjectively. The filter was extensively clinically tested: quantitative and qualitative results are reported here.
Frosio
I
I
Applied Intelligent System Laboratory, Computer Science Department, University of Milan, 20135 Milan, Italy. frosio@dsi.unimi.it
Ferrigno
G
G
Borghese
N A
NA
D000465:Algorithms; D002508:Cephalometry / Q000379:methods; D003198:Computer Simulation; D003238:Connective Tissue / Q000000981:diagnostic imaging*; D006257:Head / Q000000981:diagnostic imaging*; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D012886:Skull / Q000000981:diagnostic imaging*