Perfusion Parameter

Perfusion parameters, quantifying blood flow and volume in tissues, are crucial for diagnosing various diseases, including stroke and cancer. Current research focuses on improving the accuracy and efficiency of perfusion parameter estimation using advanced image processing techniques, particularly deep learning models like U-Nets and convolutional neural networks, often incorporating attention mechanisms and physics-informed constraints to handle noisy data and improve robustness. These advancements are leading to more reliable and efficient diagnostic tools across multiple medical imaging modalities (MRI, CT), impacting clinical workflows and potentially improving patient care.