Photoacoustic-Mr Image Registration Based on a Co-Sparse Analysis Model to Compensate for Brain Shift Publisher Pubmed



Farnia P^{1, 2} ; Makkiabadi B^{1, 2} ; Alimohamadi M³ ; Najafzadeh E^{1, 2} ; Basij M⁴ ; Yan Y⁴ ; Mehrmohammadi M^{4, 5} ; Ahmadian A^{1, 2} Show Affiliations
Source: Sensors Published:2022

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 are 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 mapping transform via a pair of analysis operators that are learned by the alternating direction method of multipliers. The method was evaluated using an experimental phantom and ex vivo data obtained from a mouse brain. The results of the phantom data show about 63% improvement in target registration error in comparison with the commonly used normalized mutual information method. The results proved that intra-operative photoacoustic images could become a promising tool when the brain shift invalidates pre-operative MRI. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.