Abstract
The tissue P system (TPS) possesses intrinsic attributes of parallel execution in comprehensive data and instruction space, which provides fast convergence during the transition from local to global optima. Method- In this study, we have proposed and built a TPSysIR framework using the TPS for image registration that optimizes upon the mutual information (MI) similarity metric to find a global solution. Result- The model was tested on single- and multimodal brain MRI scans and other prominent optimization-based image registration techniques. Conclusion- Results show that, among all methods, TPSysIR provides better MI values with minimum deviation in a range of experiment setups conducted iteratively.
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