Despite its advantages, 4D segmentation comes with several challenges. One of the primary issues is the computational complexity and high demand for processing power, which can be a limiting factor in clinical settings. Additionally, the accuracy of segmentation can be affected by motion artifacts caused by patient movement or physiological processes like breathing. Ensuring consistency across different imaging modalities and time points is also a significant challenge.
