New Pseudo-CT Generation Approach from Magnetic Resonance Imaging using a Local Texture Descriptor

One of the challenges of PET/MRI combined systems is to derive an attenuation map to correct the PET image. For that, the pseudo-CT image could be used to correct the attenuation. Until now, most existing scientific researches construct this pseudo-CT image using the registration techniques. However, these techniques suffer from the local minima of the non-rigid deformation energy function which leads to unsatisfactory results.
We propose in this paper a new approach for the generation of a pseudo-CT image from an MR image.
This approach is based on a dense stereo matching concept, for that, we encode each pixel according to a shape related coordinates method, and we apply a local texture descriptor to put into correspondence pixels between MRI patient and MRI atlas images. The proposed approach was tested on a real MRI data, and in order to show the effectiveness of the proposed local descriptor, it has been compared to three other local descriptors: SIFT, SURF and DAISY. Also it was compared to registration method.
The calculation of structural similarity (SSIM) index and DICE coefficients, between the pseudo-CT image and the corresponding real CT image show that the proposed stereo matching approach outperforms a registration one.
The use of dense matching with atlas promises good results in the creation of pseudo-CT. The proposed approach can be recommended as an alternative to registration techniques.