Automatic 3D foetal face model extraction from ultrasonography through histogram processing

Ultrasound is by far the most adopted method for safe screening and diagnosis in the prenatal phase, thanks to its non-harmful nature with respect to radiation-based imaging techniques. The main drawback of ultrasound imaging is its sensitivity to scattering noise, which makes automatic tissues segmentation a tricky task, limiting the possible range of applications. An algorithm for automatically extracting the facial surface is presented here. The method provides a comprehensive segmentation process and does not require any human intervention or training procedures, leading from the output of the scanner directly to the 3D mesh describing the face. The proposed segmentation technique is based on a two-step statistical process that relies on both volumetric histogram processing and 2D segmentation. The completely unattended nature of such a procedure makes it possible to rapidly populate a large database of 3D point clouds describing healthy and unhealthy faces, enhancing the diagnosis of rare syndromes through statistical analyses.