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

Our project aims to harness the capabilities of modern medical technology to enhance the diagnosis and treatment of brain tumors. We employ ultrasound technology in conjunction with advanced computational methods to enable more precise and efficient detection of brain tumors.

The use of ultrasound offers the advantage of being a non-invasive and cost-effective imaging modality that is well tolerated by patients. By developing and applying evolutionary algorithms, we can approximate complex perfusion models in brain tissue that are characteristic of tumors. These models allow us not only to visualize structural changes in the brain but also to analyze perfusion patterns that provide crucial information about tumor growth.

Our approach provides valuable support during surgical interventions. By integrating our ultrasound-assisted perfusion model approximation, surgeons can receive precise information about the location and extent of the tumor during the operation. This can help make surgical interventions more precise and effective by providing the ability to more accurately localize tumors and spare healthy tissue.

Overall, our project promises to improve the treatment of brain tumors by combining innovative technologies and advanced computational methods to enable precise diagnoses and enhance the effectiveness of surgical interventions.

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C / C++