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Medical image registration utilizing tissue P systems
Saleem Sanatan Kujur1, Sudip Kumar Sahana1
1Department of Computer Science and Engineering, Birla Institute of Technology Mesra, Ranchi, India.
Frontiers in Pharmacology
|August 22, 2022
Summary
The Tissue P System (TPS) framework (TPSysIR) enhances image registration by optimizing mutual information for faster convergence to global solutions. This method shows improved accuracy and consistency across various MRI scans.
Area of Science:
- Medical Imaging
- Computer Science
- Computational Biology
Background:
- Image registration is crucial for medical diagnosis and analysis.
- Traditional methods can struggle with convergence to global optima.
- The Tissue P System (TPS) offers parallel processing capabilities.
Purpose of the Study:
- To develop and evaluate a novel image registration framework, TPSysIR.
- To leverage the Tissue P System (TPS) for optimizing mutual information (MI).
- To achieve faster convergence to global optima in image registration.
Main Methods:
- Proposed and implemented the TPSysIR framework utilizing the TPS.
- Optimized the mutual information (MI) similarity metric within the TPSysIR framework.
- Tested the framework on single- and multimodal brain MRI scans.
Main Results:
- TPSysIR demonstrated superior performance compared to other optimization-based registration techniques.
- Achieved better mutual information (MI) values with minimal deviation.
- Showcased consistent results across iterative experimental setups.
Conclusions:
- TPSysIR effectively utilizes the Tissue P System for advanced image registration.
- The proposed method offers a robust solution for finding global optima in image registration.
- TPSysIR presents a promising advancement for brain MRI analysis.
