A 3D Ultrasound algorithm with alignment and nonlinearity compensation

This paper describes a system to reconstruct a 3D region of the human body from a set of ultrasound images. Several issues make this problem difficult: non uniform sampling of the 3D region, the presence of multiplicative noise (specke), the non linear compression of the ultrasound images performed during the acquisition process and image misalignment. A reconstruction algorithm is proposed which takes all these issues into account in a Bayesian framework. An interpolation model is adopted to define the acoustic reflectivity of the human tissues in the region of interest. The volume coefficients as well as the alignment and compression parameters are estimated by the minimization of a single objective function in three consecutive steps, performed in each iteration of the reconstruction algorithm. Experimental results are presented to assess the performance of the algorithm.

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