Ultrasound-assisted Perfusion Model Approximation for Cerebral Tumor Detection using Evolutionary Algorithms

Development of an innovative approach to brain tumor diagnosis and treatment by combining ultrasound technology with advanced computational methods. Using evolutionary algorithms, complex perfusion models in brain tissue were approximated, providing crucial insights into tumor growth.

The use of ultrasound offers a non-invasive, cost-effective, and patient-friendly imaging modality. Combined with algorithmic methods, it enables visualization of structural changes and analysis of perfusion patterns, delivering essential information about tumor development.

A key aspect of the project was intraoperative support. By integrating the ultrasound-assisted perfusion model approximation, surgeons receive precise information about tumor location and extent during operations. This allows accurate tumor localization and preservation of healthy tissue, significantly enhancing surgical precision and effectiveness.

Overall, this approach improves the treatment of brain tumors by combining innovative technology with advanced computational methods to enable more accurate diagnoses and enhance the effectiveness of surgical interventions.

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C / C++