Deformable prostate registration from MR and TRUS images using surface error driven FEM models

The fusion of TransRectal Ultrasound (TRUS) and Magnetic Resonance (MR) images of the prostate can aid diagnosis and treatment planning for prostate cancer. Surface segmentations of the prostate are available in both modalities. Our goal is to develop a 3D deformable registration method based on these segmentations and a biomechanical model. The segmented source volume is meshed and a linear finite element model is created for it. This volume is deformed to the target image volume by applying surface forces computed by assuming a negative relative pressure between the non-overlapping regions of the volumes and the overlapping ones. This pressure drives the model to increase the volume overlap until the surfaces are aligned. We tested our algorithm on prostate surfaces extracted from post-operative MR and TRUS images for 14 patients, using a model with elasticity parameters in the range reported in the literature for the prostate. We used three evaluation metrics for validating our technique: the Dice Similarity Coefficient (DSC) (ideally equal to 1.0), which is a measure of volume alignment, the volume change in source surface during registration, which is a measure of volume preservation, and the distance between the urethras to assess the anatomical correctness of the method. We obtained a DSC of 0.96 +/- 0.02 and a mean distance between the urethras of 1.5 +/- 1.4 mm. The change in the volume of the source surface was 1.5 +/- 1.4%. Our results show that this method is a promising tool for physicallybased deformable surface registration.