X-ray and ultrasound data fusion
This work deals with three dimensional reconstruction from X-ray and ultrasonic images. Such an issue pertains to the field of data fusion since the data provide complementary information. The two sets of data are independently related to two sets of parameters: X-ray attenuation and ultrasonic reflectivity. The fusion problem is addressed in a Bayesian framework; the kingpin of the task is to define a joint prior model for both attenuation and reflectivity. Dealing with the joint prior model, we propose to correlate the derivative of the attenuation and the reflectivity. Processing examples demonstrate the validity of the fusion approach and the robustness of the proposed method mismatching of the two sets of data.