Photoacoustic-MR Images Registration Based on Co-Sparse Analysis Model to Compensate for Brain Shift

Abstract

Brain shift is an important obstacle to the application of image guidance during neurosurgical interventions. There has been a growing interest in intra-operative imaging to update the image-guided surgery systems. However, due to the innate limitations of the current imaging modalities, accurate brain shift compensation continues to be a challenging task. In this study, the application of intra-operative photoacoustic imaging and registration of the intra-operative photoacoustic with pre-operative MR images is proposed to compensate for brain deformation. Finding a satisfactory registration method is challenging due to the unpredictable nature of brain deformation. In this study, the co-sparse analysis model is proposed for photoacoustic -MR image registration, which can capture the interdependency of the two modalities. The proposed algorithm works based on the minimization of the mapping transform via a pair of analysis operators that are learned by the alternating direction method of multipliers. The method was evaluated using experimental phantom and ex-vivo data obtained from the mouse brain. The results of phantom data show about 63% improvement in target registration error in comparison with the commonly used normalized mutual information method. Results proved that intra-operative photoacoustic images could become a promising tool when the brain shift invalidated pre-operative MRI.