4 Dimensional Medical Image

Four-dimensional (4D) medical imaging integrates three-dimensional spatial data with temporal information, enabling the visualization and analysis of dynamic anatomical changes over time. Current research focuses on improving the efficiency and accuracy of 4D image generation and analysis, employing techniques like deep learning models (including diffusion and convolutional neural networks) and novel interpolation methods to address challenges such as limited temporal resolution and data scarcity. These advancements are crucial for improving diagnostic accuracy, treatment planning (e.g., radiotherapy and cardiac procedures), and the overall understanding of dynamic physiological processes, particularly in applications like cardiovascular disease monitoring.